A Sunburnt Country

Harnessing Australia’s Most Abundant Resource

By

Alexander Laurie

A dissertation submitted in partial fulfilment of the requirements for the degree of Bachelor

of Agricultural and Resource Economics

UNE Business School

University of New England

Armidale New South Wales Australia

November 2015

ii      

Declaration

I certify that the content of this dissertation has not been submitted for any other degree and

is not currently being submitted for any other degree.

I certify that, to the best of my knowledge, any help received in preparing this dissertation,

and all sources used, have been acknowledged.

XAlexander LaurieStudent

iii    

Abstract

The Australian continent has the highest solar radiation per square metre in the world

yet Australia’s solar energy production lags behind the global proportional contribution. As

of 2014 Australia’s renewable energy accounted for less than 14 per cent of annual electricity

generation and of this amount just 0.4 per cent was attributable to large-scale solar power

generation. At the same time, the cost of solar power generation has become more

competitive than other renewable and non-renewable alternatives. Hence there is significant

growth potential for solar energy production in Australia. Large-scale solar growth will

require the selection of appropriate sites for projects, yet it is difficult to identify locations for

large-scale systems since multiple criteria must be met. This paper explains why grazing land

is likely to meet the relevant criteria and provides a landholder focused case study which

evaluates the potential implicaitons of solar leasing. An ex ante cost-benefit analysis of a

solar lease as an alternative and passive income source for cattle graziers is used to identify

the economic value for doing so. Results indicate that in most circumstances a solar lease is

able to provide a secure income source to landholders that can generate more value than

existing enterprises. When the influence of a drought is considered, the relative value of a

solar lease increases. The social benefits of solar leasing are described with reference to these

findings to provide Government policy recommendations.

iv      

Acknowledgements

I would like to thank Dr Renato Villano and Dr Stuart Mounter for their continued guidance

and ongoing support. It has been a privilege to share ideas and I look forward to further

collaboration in 2016.

I would also like to thank Trevor and Jillian Foley for helping me gain an understanding of

local grazing enterprises and for openly sharing their local knowledge.

Finally, to Angus Gemmell and the Solar Choice team I would like to express my

appreciation for their instructive advice and willingness to contribute to this dissertation.

Thank you for facilitating the simulation of this paper’s case analysis. I hope that this

research can be used as part of the project development envisaged for Armidale.

v      

Contents  

Abstract ..................................................................................................................................... iii

Acknowledgements ................................................................................................................... iv

List of Tables ........................................................................................................................... vii

List of Figures ......................................................................................................................... viii

Units & Definitions ................................................................................................................... ix

Chapter 1: Introduction .............................................................................................................. 1

1.1 Background & motivation ................................................................................................ 1

1.2 Research questions & objectives ...................................................................................... 2

1.3 Significance of research ................................................................................................... 3

1.4 Outline of dissertation ...................................................................................................... 3

Chapter 2: Background & Literature Review ............................................................................ 4

2.1 Introduction ...................................................................................................................... 4

2.2 Types of solar ................................................................................................................... 4

2.3 Solar in the world (scale & scope) ................................................................................... 6

2.4 Solar in Australia (scale & scope) .................................................................................... 9

2.5 Relevant government policy ........................................................................................... 11

2.6 Current research & development .................................................................................... 13

2.7 Challenges faced ............................................................................................................ 15

2.8 Assessment of large-scale solar in Australian Agriculture ............................................ 18

2.9 Cattle grazing & solar farms .......................................................................................... 23

2.10 Concluding comments .................................................................................................. 26

Chapter 3: Data Construction for Case Study .......................................................................... 27

3.1 Introduction .................................................................................................................... 27

3.2 Case study – Armidale 30 MW project .......................................................................... 27

3.3 Grazing enterprises ......................................................................................................... 29

3.4 Data construction ............................................................................................................ 30

3.5 Concluding comments .................................................................................................... 33

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Chapter 4: Ex ante Analysis ..................................................................................................... 34

4.1 Introduction .................................................................................................................... 34

4.2 Net present values .......................................................................................................... 34

4.3 Gross margin analysis .................................................................................................... 36

4.4 Concluding comments .................................................................................................... 37

Chapter 5: General Discussion & Conclusions ........................................................................ 38

5.1 Introduction .................................................................................................................... 38

5.2 Overview of the study .................................................................................................... 38

5.3 Summary & implications ............................................................................................... 39

5.3.1 Summary of results .................................................................................................. 39

5.3.2 Implications ............................................................................................................. 43

5.4 Areas for further analysis ............................................................................................... 45

5.5 Concluding comments .................................................................................................... 46

References ................................................................................................................................ 48

Appendices ............................................................................................................................... 51

 

 

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List of Tables  

Table 1: Generation capacities ................................................................................................. 10

Table 2: Australia’s solar farms ............................................................................................... 19

Table 3: Co-location opportunities for solar farms .................................................................. 24

Table 4: Net present value results, 2015-2035 ......................................................................... 34

Table 5: Accounting for grazing fixed costs as additional benefits for a solar lease ............... 35

Table 6: Net present value sums, including fixed costs ........................................................... 35

Table 7: Breakeven lease prices ............................................................................................... 35

Table 8: Gross margin results .................................................................................................. 36

Table 9: Comparing initial liveweight yield to drought year yield .......................................... 37

 

viii    

List of Figures  

Figure 1: Solar cells ................................................................................................................... 5

Figure 2: Solar PV cell price trends ........................................................................................... 5

Figure 3: Global renewable energy contributions ...................................................................... 7

Figure 4: Growth in solar PV capacity ...................................................................................... 8

Figure 5: Leading solar PV capacities ....................................................................................... 9

Figure 6: Australia’s renewable electricity generation composition ....................................... 10

Figure 7: Comparing renewable generation costs .................................................................... 16

Figure 8: Australia’s land uses ................................................................................................. 21

Figure 9: Transmission lines and power stations ..................................................................... 22

Figure 10: Monthly climatology of daily exposure ................................................................. 22

Figure 11: Site location ............................................................................................................ 28

 

ix    

Units & Definitions

Capacity Measurements Generation Measurements

W Watt Wh Watt hour

kW Kilowatt (1,000 W) kWh Kilowatt hour

MW Megawatt (1,000 kW) MWh Megawatt hour

GW Gigawatt (1,000 MW) GWh Gigawatt hour

The average Australian household electricity consumption is 122.3kWh/week. A 1MW

capacity solar system generates the average household’s yearly electricity demands in

approximately 6 hours.

Area Measurements

ac Acre

ha Hectare 1ha = 2.47105ac

Solar Farm: A large-scale solar system which is over 1MW in capacity.  This measurement

is provided as a guideline by the Clean Energy Council which is a nationally recognised

industry body in Australia, and can be used as a benchmark*. For the purpose of this

dissertation 1MW will therefore be used as the typical (also minimum) size of a large scale

solar project.

*It should be noted that for the market for large-scale generation certificates as a part of the large-scale renewable energy target (LRET)

systems of size over 100kW are considered large-scale

Solar irradiance: Sunlight intensity per unit area produced by the Sun in the form of

electromagnetic radiation.

Levelised Cost of Electricity (LCOE): An economic assessment of electricity generation

methods which compares different traits of comparable power sources. It is calculated as the

average total cost of development and maintenance of an asset divided by the total expected

power output, where all costs and benefits are estimated over the asset’s lifetime.

Solar efficiency: The proportion of sunlight that is captured and converted into electricity.

Photovoltaic (PV) Cell: A semiconductor diode that converts sunlight into direct current

(DC).

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Chapter 1: Introduction

1.1 Background and Motivation

It has been recognised that the current trend of energy supply is economically and

environmentally unsustainable by governments, businesses and individuals alike. In Asif and

Muneer (2007) a global energy study established that the current fossil fuel supply mix will face

many challenges: finite quantities, climate change and related environmental concerns, volatility of

fuel prices and geopolitical conflict. This knowledge has given rise to the recognition of renewable

energy sources as a means to secure energy supply and minimise social and private costs. As a

consequence renewable generation technologies have benefited from increased investment. Over

the past two decades hydro power and wind power have been able to provide the most efficient

electricity supply solutions around the world, meaning that they currently lead the renewable

resource generation mix. However, in the last five years solar energy has become just as

competitive, so investment into solar has rapidly increased. The energy efficiency of solar

technologies has quickly improved with recent developments in polysilicon thin-film and cadmium

telluride technologies and it is likely that efficiencies will continue to improve (Asif, 2007). This

identifies a significant opportunity for solar to contribute increasingly more electricity to the future

energy mix.

In Australia, solar energy contributes a relatively small portion of the nation’s total energy mix, yet

increased affordability and efficiency improvements indicate that solar will become a more

dominant energy source in the near future (Flannery, 2013). The two main types of solar

technologies which generate this energy are solar photovoltaic (PV) and solar thermal

(Concentrated Solar Power – CSP) technology. The Climate Council of Australia indicates that by

2050 solar energy is expected to provide 29% of Australia’s electricity needs, of which it is likely

that most growth will occur in the large-scale PV sector (Climate Council, 2015). Australian

households have invested heavily into rooftop PV systems. Over 1.4 million Australian households

have installed a PV system and over 2 million households use a solar thermal or PV system. On a

per capita basis, this means that Australia’s adoption of small-scale solar is greater than any other

country (Clean Energy Council, 2014). State and national government feed-in-tariffs, subsidies and

grants have encouraged this trend. By contrast there are only eight confirmed large-scale solar

projects developed or under development in Australia and there is significant potential for growth

in this area.

The development of large-scale systems requires the identification of suitable project sites. Criteria

to be met include proximity to transmission lines, solar irradiance, sunlight hours, slope, shading,

2    

zoning restrictions, fire breaks, soil type, exposure to dust and general social acceptance. It is also

important to consider the opportunity cost of using land for alternative purposes. Similarly, the

social importance of preserving wildlife systems, maintaining biodiversity and reducing other

negative externalities should be considered. The process of selecting a suitable site will be

identified in the following chapters, including an explanation of why grazing land is often suitable

for large-scale PV systems. This land can be particularly suitable for a solar alternative from a

landowner’s perspective when the low quality of existing resources limit returns from other

enterprises. This paper constructs a case study that addresses the potential for substitution of large-

scale solar with grazing land, and attempts to provide landholders with economic reasoning to

make enterprise choices in this arena.

1.2 Research questions & objectives

The ultimate goal of this dissertation is to determine whether it is beneficial for Australian

landowners (graziers) to engage with large-scale solar projects using solar lease agreements. This

involves an evaluation of the prevalence of solar in Australian at this time and an analysis of the

relevant benefits and costs to land owners. Therefore, using both primary and secondary data, this

study aims to answer what are the potential implications of solar farms for Australian cattle

graziers.

The first objective is to conduct a critical assessment of the global presence of solar technology

using secondary data sources provided by internationally recognised industry bodies. This

assessment focuses on the way Australia’s solar industry compares to those of other developed

economies and the aggregated averages for the rest of the world. The aim of this section is to show

that current reliance on solar energy as a fuel source is limited in Australia, particularly from large-

scale generation sources. Findings from this section are used to support economic analysis.

The second objective is to identify the potential value of a large-scale solar farm to a typical

Australian cattle grazing system and to an optimal grazing system using a hypothetical solar

project. By making relevant assumptions to describe a typical solar farm and the relevant grazing

systems, an ex ante analysis is conducted. A typical grazing operation for the chosen location is

used, covering 100ha. Similarly, 100ha of a highly productive benchmark grazing system is

described. Expected revenue streams and expenditures are expressed on a per hectare basis,

considering gross margin per hectare as a key variable. Cost-benefit analysis evaluates the potential

value of a 100ha solar farm against these two types of enterprises using income streams relevant to

a solar lease agreement. Revenue flows for cattle operations and solar leasing are projected and

3    

discounted to a present value. The findings of this economic analysis are then used to describe the

situations in which a cattle grazing enterprise may be substituted with a solar farm to supplement

farm income.

1.3 Significance of research

This research is significant for two key reasons. Firstly, it identifies solar energy as an affordable

renewable energy alternative with significant potential to become a primary fuel source for

Australia. This is achieved by showing that Australia’s adoption of solar has been rapidly outpaced

by other developed economies, particularly for large-scale systems. This builds a framework to

determine how the country may invest in large-scale solar – by identifying suitable locations. An

assessment illustrates that grazing land is often suitable for such projects and ex ante economic

analysis shows landholders why it can be beneficial to explore the options of solar leasing. In doing

so cost-benefit analysis shows that when specific conditions are met landholders can utilise solar

leasing as a secure, passive income source which provides social and private benefits. These

findings may help solar developers identify landholder benefits so that they can build relationships

with landholders that enable the establishment of large-scale solar systems.

1.4 Outline of dissertation

The following chapter includes a literature review which contextualises global renewable energy

production trends, focusing on solar energy. Australia’s current use of solar energy is described

with reference to global solar energy trends. Australia’s solar industry is dissected between large

and small scale technologies. This highlights the current status of large-scale solar PV generation in

Australia and provides a platform for a case study analysis in Chapter 4. The third chapter explains

how data is constructed to facilitate financial analysis which can provide landowners with

economic reasoning to make enterprise decisions. Chapter 4 conducts an ex ante evaluation to

determine the private economic value of the described project under certain circumstances. In doing

so the analysis discounts future outcomes, providing relevant landowners with an estimation of

revenue streams over a 20 year period. This information is used in the final chapter to recommend

possible enterprise choices. The appropriateness of each choice is discussed, as are the implications

for policy makers.

4    

Chapter 2: Background & Literature Review

2.1 Introduction

The purpose of this chapter is to conduct a critical assessment of existing literature to

identify current trends in the development of renewable energy. This assessment is used to identify

growth in the global solar PV industry. By establishing that future growth is likely to occur in the

large-scale PV sector in Australia the usefulness of this paper’s case study analysis is justified.

Renewable energy is broadly defined as energy which can be obtained from natural resources that

can be constantly replenished (Australian Renewable Energy Agency, 2015). A number of these

resources exist in abundance, which are classified by the following groups; bioenergy, geothermal

energy, hydropower, ocean energy, solar energy and wind energy. The prevalence of energy

conversion technologies for each resource is largely dependent upon the availability of the natural

resource and the cost of harnessing its energy. Economies of scale and technological advancements

have been realised throughout the renewable energy sector, enabling renewable technologies to

produce electricity at production costs competitive with fossil fuels (Climate Council, 2015).

Energy created from heat from the Sun or sunlight directly is known as solar energy. This energy

can be converted into electricity or be used directly for heating/cooling. The two main methods of

solar energy conversion are briefly explained in the following section.

2.2 Types of solar

Solar PV is the dominant solar technology in Australia. Using photovoltaic cells sunlight is

converted directly into electricity – sunlight energy strikes the semiconductor material contained

within the cell which triggers the release of electrons. Electrical conductors can be used to capture

the movement of electrons (electricity) (Knier, 2002). Common semiconductors used in the

marketplace are Crystalline Silicon and Cadmium Telluride. Multiple PV cells can be connected to

form a module and an array of modules can be used to construct a PV power system (Figure 1),

converting energy from sunlight to direct current (DC) electricity. DC electricity can then be

converted to alternating current (AC) electricity using an inverter. PV systems can be connected to

existing electricity networks or batteries so that electricity is available in the absence of sunlight.

5    

Figure 1: Solar cells

Source: (Wood, 2015)

Whilst solar PV technologies were first developed in the 1950’s the growth of solar PV as an

electricity source has been constrained by production costs. The cost of components required and

the availability of key resources have led to large upfront costs, thus hindered large scale entry to

energy markets. Consequently, the adoption of solar technologies has historically been limited to

small scale private systems. It is only over the past decade that technological innovations and the

realisation of economies of scale have allowed large scale adoption by energy networks around the

world. The following figure shows how the price of PV cells purchased from silicon cell

manufacturers has changed:

Figure 2: Solar PV cell price trends

Source: (Bloomberg New Energy Finance, 2015)

Government subsidies, feed-in-tariffs and other polices have played a crucial role in facilitating

solar PV’s entry to energy markets. The entry of solar PV is however, competing with the entry of a

second solar technology – Solar Thermal.

0  

10  

20  

30  

40  

50  

60  

70  

80  

$/wa%

 

Price  history  of  silicon  PV  cells  in  US$/wa%  

6    

Concentrated Solar Power/Solar Thermal (CSP) involves the conversion of sunlight energy into

thermal (heat) energy. Lenses and tracking mirrors can focus large areas of sunlight into a small

beam. CSP systems are often used to heat air, water and other fluids (e.g. solar hot water systems).

They can also be used to power refrigeration cycles for cooling purposes and to heat steam to

power electricity-generating turbines. Generally, large scale CSP systems are considered to be more

efficient (’00/’000 megawatts and above) than PV systems. CSP Systems are however, relatively

more expensive to install than equivalently yielding PV systems (Australian Renewable Energy

Agency, 2015). These technologies have a significant advantage in that heat/energy can be stored

more easily than a PV system, thus can supply energy more efficiently through peak and off-peak

usage periods. The three main types of CSP systems are the parabolic trough system, the solar

tower (central receiver plant) and the parabolic dish plant (Boruff, 2010).

The hypothetical solar system identified in Chapter 3’s analysis is that of a PV system, in which

96,780 solar modules are arranged in a fixed array (refer to Appendix 1 for Solar Choice 30MW

solar farm output). It is important to note, however, that a similar yielding CSP system covering

100ha could be used. The use of CSP as an alternative requires further research which is beyond the

scope of this dissertation.

2.3 Solar in the world (scale & scope)

It should be borne in mind that the quality of data coverage from international bodies is variable,

given the small scale of many generation projects and access to reliable energy statistics.

Nonetheless, publications from internationally recognised bodies such as the Renewable Energy

Policy Network (REN) can be used to identify general trends. The 2014 Ren21 Global Status

Report indicates that renewable energy had accounted for around 22.1% of global electricity

production in 2013 and that this share would continue to increase over the coming years (REN21,

2014). Of that 22.1% in 2013 it was estimated that around 16.4% was accounted for by

hydropower, 2.9% wind power, 1.8% bio-power, 0.7% solar PV. The remaining 0.4% was

attributed to geothermal, CSP and ocean power (Figure 3). Whilst renewable power generation

capacity is still exceeded by fossil fuel and nuclear it is important to note that renewable energy

sources are attracting policy and investment support and are the dominant supply source to yearly

growth in global electricity demand – in 2013, 56% of net additions to global power capacity were

made up of renewables (REN21, 2014).

7    

Figure 3: Global renewable energy contributions

Source: (REN21, 2014)

Solar technologies contributed to both heat and power energy classes and the report noted that from

2009 to 2013 solar PV experienced the fastest capacity growth rate of all energy technologies

(Figure 4). Over the year of 2013 solar PV accounted for about one-third of renewable energy

capacity added globally.

8    

Figure 4: Growth in solar PV capacity

Source: (REN21, 2014)

Over the past 10 years multiple leading world economies have invested in solar PV as a primary

electricity generation source (Figure 5). Germany now generates the most electricity from solar PV

with 21.2% of the global share of installed PV capacity. China, Japan, Italy and the United States

generate 15.6%, 12.9%, 10.2% and 10.1% respectively (REN21, 2015). Australia’s installed

capacity share is far less at 2.3%, yet this exceeds the installed capacity of economies of similar

size such as Canada which has 0.9% of the world share. The 2015 Ren21 Global Status Report also

notes that as of 2015 over 60% of all current PV capacity has been developed over the past three

years. This illustrates global confidence in solar energy as a long term investment for renewable

energy supply.

9    

Figure 5: Leading solar PV capacities

Source: (BP plc, 2015)

This evidence could be used to suggest that the general uptake of small and large-scale solar in

Australia is limited. The following section explains why this is not entirely accurate, given

Australia’s rapid investment into small-scale solar systems at the private household level.

2.4 Solar in Australia (scale & scope)

The Australian continent has the highest solar radiation per square metre in the world, therefore

significant potential to harness solar resources (Geoscience Australia, 2015). The highest

concentrations of solar radiation are in the desert regions in the northwest and centre of the

continent. Australia receives an average of 58 million petajouls (PJ) of solar radiation per year –

approximately 10 000 times more than its total energy consumption. The current reliance on solar

energy sources however, is much less than most other developed nations. In 2014 renewable energy

met 13.47% of Australia’s electricity needs while the global average utilisation of renewables was

greater than 20% (Clean Energy Council, 2014). Figure 6 illustrates the breakdown of this 13.47%

between various renewable sources. Of this portion around 16% is attributable to the variety of

solar energy sources, for which 15.3% is from household and commercial solar systems (Table 1).

Australia’s solar contribution is dominated by this sector as 1.4 million Australian households have

installed solar panels on their roofs since 2001 (Wood, 2015). The Clean Energy Council (CEC)

indicated that household solar outpaced the large-scale sector because consumers sought to reduce

10    

soaring electricity costs and awareness about climate change and the benefits of solar energy

improved.

Figure 6: Australia’s renewable electricity generation composition

Source: (Clean Energy Council, 2014)

Table 1: Generation capacities

Technology Generation (GWh)

Share of renewable generation

Share of total generation

Equivalent number of households powered/year

Hydro 14,555 45.9% 6.19% 2,049,900 Wind 9,777 30.9% 4.16% 1,377,000 Small-scale solar

4,834 15.3% 2.06% 680,900

Bioenergy 2,400 7.6% 1.02% 338,000 Large-scale solar*

118 0.4% 0.05% 16,700

Geothermal 0.50 0.002% 0.00% 70 Marine 0.04 0% 0.00% 6 TOTAL 31,684 100% 13.47% 4,462,600

*includes large scale solar PV and solar thermal. Source (Clean Energy Council, 2014)

The Australian Climate Council has estimated that solar power generation will continue to grow,

contributing 29% of Australia’s electricity needs by 2050 (Climate Council, 2015). It is likely that

this growth will occur in the large-scale PV space. The Australian Renewable Energy Agency

(ARENA) has indicated that investment into large-scale photovoltaics is one of the Australian

Government’s five priorities for new investment. Moreover, Kane Thornton – Chief Executive of

the CEC, noted that large-scale solar PV generation systems are “at an early stage of development”

11    

and that there is “significant potential for growth” (Clean Energy Council, 2014). These views and

the current assessment of large-scale PV’s presence suggest that the development of such projects

in the future is inevitable.

2.5 Relevant government policy

There are a variety of government support programs for renewable and solar energy specifically

designed to: encourage research and development, provide finance for projects, assist renewable

energy uptake and to set long term growth goals. To date the Australian government has developed

policies to price carbon, set renewable energy targets, implement feed-in tariffs and has provided

direct financial support.

Feed-in tariffs are widely used in developed economies for the uptake of renewable technologies,

being particularly useful for the uptake of small-scale rooftop solar PV in Germany and the United

States. The Australian Government has also used such tariffs whereby households and businesses

owning small-scale generation systems have been paid for their generation of renewable electricity,

providing credits for each unit of renewable electricity generated or sold to the grid. Gross feed-in

tariff schemes and net feed-in tariff schemes offer varied prices for credits, both of which have

been employed by Australian governments at a state level. These tariffs have prompted Australian

households to invest in small scale rooftop PV systems, contributing to the large portion of

generation capacity shown in Figure 7. Australians took advantage of these tariffs more rapidly

than expected in the early 2010’s, reducing national demand for electricity. Consequently the

Federal Government has urged State Governments to phase out such tariffs and focus on the

development of large-scale renewable technologies (Renew Economy, 2015). This pressure may

also influence the effectiveness of carbon pricing as renewable energy policy increasingly focuses

on large-scale developments.

Carbon pricing effectively places a social price on the consumption of fossil fuels. This makes

fossil fuels relatively more expensive than renewable alternatives. By doing so the government is

attempting to redirect energy investment away from non-renewable resources to clean energy

alternatives. To do so the production of carbon is taxed, to raise revenue that can be reinjected into

renewable energy support programs. This allows market participants which emit carbon to find

innovative ways to source low-emissions energy (Climate Council, 2015), therefore reducing

overall carbon emissions and prompting businesses to invest in renewable energy. Australia

introduced a carbon price commonly known as the ‘Carbon Tax’ under the Labour Party yet it was

repealed when the government changed in July 2014 (Griffiths, 2014). This made previously taxed

12    

carbon-based assets relatively cheaper to consume, reinvigorating Australia’s use of fossil fuels for

electricity generation. This move caused non-renewable alternatives to seem relatively less

expensive. It is only through the revision of the Renewable Energy Target (RET) that these losses

have been recovered.

The objective of the RET is ‘to advance the development and employment of renewable energy

resources over the medium term and to assist in moving Australia to a lower carbon economy’

(BREE, 2014). This Federal Government policy was introduced in 2010 to ensure that at least 20%

of Australia’s electricity is produced from renewable sources by 2020. As a part of this policy

legislation was designed that required the RET to be reviewed every two years. Initially it was

thought that 20% of Australia’s annual electricity demand would equate to around 45,000GWh by

2020, so the 2010 policy targeted this figure. Since 2010 however the availability of increasingly

energy efficient appliances, decline in growth of some energy intensive industries (metals &

mining) and the rapid uptake of rooftop solar PV has reduced the national demand for electricity.

Consequently the initial RET target was deemed to have overstated the portion of power supply

that should be provided using renewable energy sources. It is for this reason that two-yearly

reviews have led to the downward revision of the RET. As of June 2015 the target has been

reduced to 33,000GWh (Clean Energy Council, 2015). Prior to this decision ongoing uncertainty

surrounding the RET hindered investment into renewable energy. As such the addition of large-

scale projects over the period 2012-2014 was limited. Bloomberg New Energy Finance estimated

that new investment in large-scale projects such as solar farms reduced by 88% over the 15 month

period that the RET was reviewed. As a part of this year’s review policy makers also removed the

previously legislated reviews required for the RET, meaning that the current target will remain

unchanged until 2020. It is only now that the RET has been finalised that investors can confidently

seek renewable energy opportunities in a more bankable, secure environment. For investors looking

to do so it is important to distinguish between the two components of the RET; the Large-scale

Renewable Energy Target (LRET) and the Small-scale Renewable Energy Scheme (SRES).

The Clean Energy Council explains the SRES as a policy which promotes the installation of

eligible small-scale renewable energy systems by providing a financial incentive to do so. It does so

through the creation of small-scale technology certificates which RET liable entities have a legal

obligation to buy and surrender to the Clean Energy Regulator on a quarterly basis.

The LRET similarly creates a financial incentive for the development of renewable energy

generation systems of capacity greater than 100kWh. A market for large-scale generation

certificates has been created for which developers can sell large-scale generation certificates to

RET liable entities. Large-scale developers can, however, sell electricity directly to the grid. The

13    

Clean Energy Council estimates that the majority of the additional 6GWh of renewable capacity

required by 2020 will be provided by between 30-50 major large-scale projects. It can be assumed

that these developments will be dominated by the currently cost-competitive renewable sources:

wind and solar. Since June this year three large wind energy projects and two large solar energy

projects have been approved. Relevant projects are listed and further discussed in the latter part of

this chapter.

Direct financial support continues to be provided to renewable energy projects, research and

relevant investments. This support can be provided through competitive government grant

programs, related investments and donations. Examples of industry bodies which provide such

support are The Clean Energy Finance Corporation (CEFC) and the Australian Renewable Energy

Agency (ARENA). ARENA is an industry body which provides financial support for renewable

energy research and development. ARENA intends to run a competitive solar grant program for up

to 200MW of large-scale solar PV. Proposals will be expected to be between 10MW and 50MW

(DC) and have a levelised cost of electricity (LCOE) of $130/MWh or less (Australian Renewable

Energy Agency; ARENA, 2015). The goal of this funding support will be to substantially reduce

the current gap in commercial competitiveness between large-scale solar PV and wind generation.

Similarly to ARENA, the CEFC released a report in September 2015 outlining a competitive grant

program which is aimed at ‘encouraging greater participation in the large-scale solar sector in

Australia’ (Clean Energy Finance Corporation, 2015). This $250 million program is designed to

help solar retailers reduce the cost of solar development and bolster supply chains. In addition to

CEFC and ARENA funding the solar industry continues to benefit from direct investment from

various public and private companies seeking to invest in an alternative energy future.

Interestingly, Fotowatio Renewable Ventures (FVR), owner of the Royalla and Moree Solar Farms

(Table 2, page 19), has recently been purchased by Saudi Arabia-based conglomerate Abdul Latif

Jameel Energy – a natural resources conglomerate. This may be indicative of a turning point for

investment into electricity generation resource asset classes. Nonetheless, private sector investment

will continue to encourage government policy makers to develop appropriate renewable energy

policies.

These various Government policies will be discussed at an international forum in November 2015

at the Global Climate Summit in Paris. Australian representatives will attend the summit and it is

possible that a strong message will be conveyed for the support of large-scale wind and solar

projects. It is very likely that discussions in this area will find that additional research and

development should be dedicated to these industries.

14    

2.6 Current research & development

Australian researchers regularly contribute to developments in solar PV and CSP technologies. A

variety of research has been recognised internationally for ground-breaking developments over the

past 75 years, dating back to the world’s first solar hot water system which was developed by

Australian scientists in 1941 at the Commonwealth Scientific and Industrial Research Organisation

(CSIRO). Since then Australians have produced highly efficient solar cells, breaking international

records for efficiency. The Australian Photovoltaic Institute (APVI), CSIRO, ARENA, CEC and

leading Australian universities all undertake solar research which continues to provide innovative

and efficient solar technology to the national and international markets. Notably, the University of

New South Wales (UNSW) provides world leading research, having very recent success improving

PV cell efficiency.

Solar cell researchers from the UNSW have set consecutive efficiency records since the early

1980’s and continue to do so. This research continues to be supported by ARENA and the

Australia-US Institute for Advanced Photovoltaics (AUSIAPV). In December 2014 UNSW’s solar

researchers reported the highest ever sunlight conversion efficiency in the world. Using a

commercially available solar cell on the current market the researchers were able to concentrate

sunlight with an optical bandpass filter which captures sunlight that would normally be wasted

(UNSW, 2014). In doing so 40% of the sunlight hitting the cell was converted into electricity, the

highest efficiency ever recorded. The technology was independently tested by the National

Renewable Energy Laboratory (NREL) in the United States and confirmed to be the most efficient

conversion of solar energy in the world (UNSW, 2014). This achievement has far reaching

implications for the current solar industry, since the new technology can be built around existing

solar PV infrastructure. If optical bandpass filters become commercially available to solar

developers the generation capacity for existing solar systems could double or triple in size,

depending on the technology used. This could increase system yields, relatively decrease the LCOE

and reshape Australia’s renewable energy industry. There is significant potential for this

technology to do so, but continued research will be required to determine the most cost-effective

means for integration with existing and future PV systems.

Ongoing solar cell research continues to attract investment in Australia and around the world.

Being the world’s sunniest nation with an international reputation for world leading research, it is

hoped that this investment will continue to improve solar cell efficiency to provide the market with

cheap solar energy alternatives (Flannery, 2013).

15    

2.7 Challenges faced

Whilst solar technology is rapidly increasing its capacity, the industry faces a number of challenges

at a global scale. Dr. Faith Birol, chief economist of the International Energy Agency (IEA) named

subsidies for fossil fuels as “public enemy number one to sustainable energy development”.

Subsidies for nuclear power and fossil fuels are estimated to be valued between USD 544 billion

and USD 1.9 trillion, depending on calculation methodology. Financial support for renewable

energy is much lower at around six times less, yet solar PV receives about 73% of this financial

assistance (REN 21, 2013). The IEA suggests that this hurdle will be naturally overcome as the

world economy transitions away from fossil fuels towards renewables, yet it is unlikely that

renewables will become the dominant source of global electricity supply until 2050 (REN21,

2015). Australia subsidises fossil fuels through a variety of Government programs, including diesel

fuel rebates, accelerated depreciation on exploration and accelerated depreciation on mining assets.

As such it is estimated that the Federal Government will spend approximately $13.85 billion in the

next four years on these subsidies (Milne, 2015). These subsidies facilitate the development of

fossil fuel industries and decrease the levellised cost of producing electricity from fossil fuel

resources. Whilst these subsidies remain in place the uptake of renewable alternatives will continue

to be hindered, unless renewables are able to decrease cost efficiencies further. It is for this reason

that the Australian solar industry will continue to be challenged by such subsidies as Dr. Birol

would suggest. Ceteris paribus, solar PV may be able to do so if cost-competitiveness remains

strong at levels shown earlier in Figure 2.

Similar to the challenge posed by subsidies to non-renewable resources, Australia’s solar industry

is directly challenged by the fossil fuels themselves. Australian electricity providers will naturally

seek to produce electricity at the lowest possible cost, thus, use coal and natural gas sources if they

continue to be cheaper. Coal remains Australia’s cheapest electricity generation resource, closely

followed by natural gas. Solar’s competitiveness against these fuels will continue to be dictated by

variations in upfront capital costs, maintenance costs, fuel costs and overall LCOE. The long term

advantage renewables hold over the non-renewables is the knowledge that fossil fuels exist in finite

supply, whilst renewables may be constantly replenished. In mid-2015 the G7 leaders announced

that they had agreed to phase out the use of fossil fuels sometime this century, a milestone which

indicates that the transition away from fossil fuels is gaining certainty.

In addition to competition against fossil fuels, solar energy also competes with other renewable

energy sources. Rather than competing for access to resources, space or specialised skills the

renewable energy generators are competing to provide clean energy at the lowest possible cost. The

International Renewable Energy Agency (IRENA) summarises typical ranges and weighted

16    

averages for the total installed costs of utility scale renewable power generation technologies by

region in their Renewable Cost Database (Figure 7).

Figure 7: Comparing renewable generation costs

Source: (IRENA, 2015)

Australia, an OECD nation, exhibits sector competitiveness similar to that shown in the central

panel above. Onshore wind and hydropower systems have previously been the most competitive

generation technologies – explaining why Australia’s renewable energy generation composition is

as shown in Figure 6. Recently though, solar PV has improved cost efficiency. Between 2008 and

2014 the average solar PV LCOE in Australia is estimated to have fallen between 42-64% (IRENA,

2015). In conjunction, IRENA predicts that the industries with the largest remaining cost-reduction

potential are CSP, solar PV and wind. Coupling the realised cost reductions with IRENA’s

predictions it becomes clear that solar PV is in a strong position to challenge the traditional utility

model used in Australia.

Even though this outlook is positive, solar has been challenged by the lack of battery storage

technology and will continue to require improved storage technology to store larger capacities of

electricity. Prior to recent storage developments, solar generation suffered from an inability to meet

peak power demand periods throughout the day. Over the last three years though, battery storage

capabilities have improved markedly. Tesla’s introduction of the Powerwall – a wall mounted

17    

battery system which can be integrated with a household’s existing solar PV system and

corresponding gigafactory to produce them is among the most significant developments (TESLA,

2015). In today’s marketplace a variety of battery applications are available to consumers willing to

pay for the technology. Utility scale aggregations of such technology are also available for large-

scale solar systems. This has alleviated the peak-demand supply issue, yet poses the possibility of

homeowners reducing their reliance on the grid. Energy independence would decrease national

demand for grid-based electricity further and challenge the industry to reconsider the future of grid-

supply sources, such as large-scale solar PV. If batteries could be cheaply purchased and integrated

with existing systems the global utility based generation model would become redundant.

Bloomberg Business released a report in June 2015 commenting on this challenge, finding that it is

unlikely that solar energy battery storage will become cheap enough for households to adopt

(Bloomberg Business, 2015). Nonetheless the existing utility model will continue to be exposed to

the risk of redundancy if batteries can be produced with greater cost-efficiency.

The suggestion that large-scale solar is directly challenged by the risk of grid independence implies

that consumers would be willing to invest in small-scale PV systems to take advantage of battery

technology. This implication is exposed to the risk of solar losing social acceptability as a

generation source. A 2015 ARENA/Ipsos study identified solar energy as having a social licence to

operate, particularly more so than wind energy (ARENA/Ipsos, 2015). The study found that solar is

currently seen as a socially acceptable technology in terms of: reliability and efficiency, visual

appearance, environmental impacts, economics and employment and health impacts. 78% of

participants indicated that they are in favour of large-scale solar, whilst 87% indicated that they are

in favour of rooftop PV (ARENA/Ipsos, 2015). Evidently solar PV is not immediately challenged

by levels of social acceptance. Nonetheless, materials used for solar cells may prove to have long

term externalities which have not yet been realised. The future social acceptance of solar could vary

but the current attitudes toward large and small-scale PV suggest that this risk is unlikely.

A challenge particularly relevant to large-scale PV is the knowledge gap between current and

required skilled human capital for development. A 2012 project scope report produced for AGL’s

Energy Solar Project (Nyngan and Broken Hill Solar Plants) identified some current and possible

future challenges for large-scale projects. Firstly, the skills for construction and specialised

engineering design necessary for the development of large-scale solar projects are somewhat

limited in Australia. In 2014 the Clean Energy Council and Australian Bureau of Statistics

estimated that only 543 people worked in the large scale solar industry (Clean Energy Council,

2014). In conjunction, the scope for specialised skills required for the delivery of grid connection

assets (substations and transmission lines) may be too large for a single contractor (AGL, 2014).

18    

The market for large scale solar projects may need to mature before the types of contractors that

can offer the entire scope of specialised skills develop. AGL indicated that it would be

advantageous for future projects to use a single engineering, procurement and construction (EPC)

contractor to deliver all the work. However, it should be acknowledged that this challenge should

be considered alongside the demand for specialised skills and costs.

Assuming that these challenges are overcome the development of solar farms will still be limited to

the selection of an appropriate location. This limitation poses a significant challenge to the

development of solar farms. When selecting a suitable location the solar developer must consider

the relevant criteria to be met for the chosen project size. Firstly, proximity to existing transmission

lines and substations should be considered – and the power capacity of the project should be

matched with the transmission capacity of nearby electricity networks. Access to a substation

directly reduces the developer’s expense of building a substation for the purpose of the project.

Similarly, close proximity to a substation keeps expenditure on transmission lines (overhead power

lines or otherwise) to a minimum. It is for this reason that the solar farms listed in Table 2 (page

19) have been constructed in close proximity to transmission networks and existing substations.

Using known transmission infrastructure locations as a guide, a developer can then identify areas of

land large enough for the relevant size of solar farm. The developer needs to consider climatic

conditions for sunlight hours and irradiance (for generation yield) and topographic traits of possible

locations. Land should be relatively flat, cleared, have a northern aspect, not overlap restricted

zoning areas, have minimal risk of bushfire or flooding and have an appropriate soil structure. Once

a suitable location is determined the solar developer must identify the current land use of the area

so that the opportunity cost of constructing a solar farm can be considered. A developer should also

consider the intrinsic value of the land for a variety of existing or possible land uses, with the

attendant public interest attached to this.

An aggregation of these limiting variables shows that it is difficult to identify suitable locations for

large-scale solar systems, particularly as system sizes increase. To solve this problem solar

developers have sought to integrate, co-locate and substitute land areas with landholders situated in

suitable locations with large enough areas of land to facilitate large-scale solar PV – Australia’s

primary producers.

2.8 Assessment of large-scale solar in Australian Agriculture

The increased scale of a solar farm and its location in a high intensity sunlight area improves both

the yield of energy output and overall energy production. Even though Australia receives more

19    

sunlight per square metre than any other country in the world, the utilisation of this resource at a

large scale is significantly underdeveloped. The CEC estimated that existing projects contributed to

0.4% of total energy generated in Australia in 2014. This portion is primarily contributed by the

operational (commissioned) solar systems shown in Table 2.  

Table 2: Australia’s solar farms¹ Technology Owner Location Capacity

(MW) Status (2015) Existing/previous

land use² Solar PV Solar Chocie Bulli Creek,

QLD 2,000 Planning Cattle grazing

Solar PV AGL Nyngan, NSW 102 Commissioned (2015)

Cattle grazing and dryland cropping (mixed)

Solar PV Fotowatio Renewable Ventures

Moree, NSW 56 Under construction

Cattle grazing and dryland cotton cropping

Solar PV AGL Broken Hill, NSW

53 Under construction

Cattle grazing

Solar Thermal

CS Energy Kogan Creek, QLD

44 Under construction

Native bushland (required clearing)

Solar Thermal

RATCH-Australia Collinsville, QLD

30 Planning Native bushland (requires clearing)

Solar PV Fotowatio Renewable Ventures

Royalla, ACT 20 Commissioned (2014)

Cattle and sheep grazing

Solar PV Synergy/GE Greenough River, WA

10 Commissioned (2012)

Cattle and sheep grazing, irrigated cropping

Solar Thermal

Areva/Macquarie Generation

Liddell III, NSW

9.3 Commissioned (2012)

†

Solar PV Belectric Mildura, VIC 3.5 Commissioned (2014)

†

Solar PV First Solar/University of Queensland

University of Queensland, QLD

3.275 Under construction

†

Solar PV Silex (Solar Systems) Mildura Stage 1, VIC

1.5 Commissioned (2013)

†

Source: (Clean Energy Council, 2014)

¹Not an exhaustive list of Australia’s large-scale PV systems. This table summarises the five largest operational plants (commissioned) as well as seven large projects which are being developed - identified by the Clean Energy Council ²Land use identified in corresponding environmental impact statements †Land use for projects smaller than 10MW varies significantly

The land area required for the solar farms listed in this table varies for the specific types of

technology used in the system. This depends on the type of technology available and the climatic

conditions for the specific location. In order to determine which technology should be used for a

specific location and the amount of land required developers can conduct private research or invest

in solar consulting/brokering services. Solar Choice is a Sydney based solar broker which provides

such services, and has provided relevant information for the purpose of this analysis; typically,

20    

either horizontal single access trackers or fixed PV panels will be used. Horizontal single access

trackers require approximately 3 hectares of land area per megawatt of capacity, whilst fixed panels

require 2-3 hectares for the same capacity system. Land area is also required for the relevant

transmission infrastructure to connect to the nearest electricity network. This means that in total

approximately 100 hectares of land is required for each 30MW of capacity (Gemmell, 2015).

Considering the aforementioned criteria the number of possible locations for a solar farm quickly

diminishes. There are many large transmission nodes in Australia’s urban centres yet multiple

blocks of land would need to be aggregated to obtain the appropriate scale of land required for a

project. Furthermore the opportunity cost of using land in these areas for private and public

developments can be significantly higher than areas of land in regional areas (Solar Choice, 2015).

Regionally located marginal land which is only suitable for agricultural enterprises that does not

have a foreseeable opportunity cost for alternative land uses (such as mining) is therefore the most

suitable. Intuitively it would be thought that land of the lowest productive quality located in the

desert regions of Australia where sunlight intensity is highest is where these criteria would be best

met. The issue however is proximity to existing transmission networks and substations of large

enough capacity to supply enough electricity to the grid. Generation capacities need to be matched

with load capacities for existing infrastructure, meaning that large-scale applications are limited to

certain locations. Similarly the capital cost of installing transmission lines to connect a project to

the grid is approximately $1M/km (Gemmell, 2015). Proximity to a substation of a suitable

capacity is evidently very important to the capital requirements of a project.

An assessment of the chosen locations for some of Australia’s largest operational and planned solar

farms is conducted to identify which types of land have previously been identified as being suitable

for large-scale PV developments. From Table 2 it can be seen that solar farms have been

constructed on a variety of different land areas around Australia, used for cattle and sheep grazing,

dryland and irrigated cropping, and native bushland. In most cases land has previously been used

for grazing purposes to some degree (or still is). Environmental impact statements made publically

available provide this information, yet do not specify the types of grazing or cropping enterprises

used. Further research and consultation with previous and existing landowners could be used to

gather this information. Regardless, it is important to note that cattle grazing enterprises are

commonly situated in areas suitable for solar farms. There are many reasons why this is the case.

As was previously mentioned, solar farms require large areas of land – approximately 100 ha per

30MW of capacity for a PV system. Similarly, close proximity to a transmission line or substation

minimises expenses required to connect to the grid. Climatic conditions have to be suitable,

particularly those for solar irradiation and sunlight hours. Land should be relatively flat or have a

21    

slightly northern aspect and be free from restricted zoning areas. The areas of land which suit these

initial criteria best are in central and western New South Wales, and eastern South Australia

(Figures 9 and 10). Figure 8 shows that livestock grazing and dryland agriculture are the primary

land uses for these areas. Dryland agriculture, however, often utilises highly fertile soil types for

various cropping enterprises. It may be found that this land is well suited to such enterprises and

that the opportunity cost of substituting cropping area for solar farming is too high. In conjunction,

fertile black soils present within dryland agriculture zones are unsuitable for large-scale solar

systems. These soil structures can be highly porous and subject to textual variation which inhibits

the soils ability to provide firm support for a solar array. Dryland agriculture zones are therefore

less suitable than grazing land, yet they may still be used if specific conditions are met.

Additionally, a location’s suitability will also be influenced by the risks associated with floods,

fires, dust and pollution. These risks can be assessed on a case-by-case basis and are important

considerations for the longevity of a solar farm.

Figure 8: Australia’s land uses

Source: (Department of The Environment, 2001)

22    

Figure 9: Transmission lines and power stations

Source: (LLNSW, 2015)

Figure 10: Monthly climatology of daily exposure – direct normal exposure

Source: (ARENA, 2015)

23    

2.9 Cattle grazing & solar farms

Around the world, solar farms are increasingly being developed on land that supports other grazing

enterprises. The technology offers opportunities for a variety of multipurpose and mixed land uses.

Co-location applications for solar PV have been studied and applied in the United States, co-

production of meat and solar energy has been trialled in Japan, German developers have invested

heavily in solar lease agreements and in India solar PV has been considered for deployment above

canals to reduce evaporation rates and supply grazing enterprises with irrigation for pasture

improvement (Ferroukhi, 2015). The practicality of applying these models to a grazing system

varies. An assessment of the possible interactions between solar farming and grazing is used to

suggest how Australian cattle graziers can integrate existing enterprises with solar farming. Whilst

assessing options for co-location and solar leasing it should be borne in mind that a solar developer

can choose to purchase land directly, negating the need for this analysis. Similarly, a landowner

may choose to develop a solar farm independently from existing enterprises. This analysis is useful

for developers and landowners who seek to avoid large upfront capital expenses for land and

infrastructure, to instead suggest alternate financing options.

Research related to the co-location of large-scale solar systems with grazing enterprises in Australia

is somewhat limited. It is probable that relevant research will be undertaken as Australia’s uptake

of large-scale PV grows. To gain an understanding of co-location opportunities it is therefore useful

to consider research conducted in parts of the world where the uptake of large-scale PV is greater.

A study prepared by Macknick (2014) for the United States National Renewable Energy

Laboratory (NREL) provides a useful summary of integration opportunities. It was found that solar

infrastructure could be strategically placed above a vegetation area so that average vegetation

yields were not substantially affected. Benefits for doing so were not quantified. Rather, qualitative

observations of existing solar farms were used to indicate opportunities. The implications of the

study’s findings for grazing enterprises are significant, particularly for small-animals such as sheep,

goats and free-range poultry. Table 3 summarises the three varied co-location opportunities

identified by this study.

24    

Table 3: Co-location opportunities for solar farms

Land-use Co-location Opportunities

Grazing*

Energy Centric: -­‐ Leave vegetation intact -­‐ Plant short shade-tolerant crops

Vegetation Centric: -­‐ Leave vegetation intact -­‐ Plant mix of sun-loving and shade-tolerant crops -­‐ Elevate solar infrastructure -­‐ Space out solar infrastructure -­‐ Continue/initiate grazing activities

Integrated Vegetation-Energy Centric: -­‐ Leave vegetation intact -­‐ Plant short shade tolerant crops -­‐ Elevate solar infrastructure -­‐ Continue/initiate grazing activities

*Grazing land slope of 1-5%. Source: (Macknick, 2014)

Incorporation of elevated solar infrastructure was found to have been used in two main ways as

shown above, where energy centric systems focus on solar energy yields per hectare and vegetation

centric systems focus on grazing yield. It was noted that these models could potentially be used to

provide diversified revenue from small-animal grazing enterprises where high vegetation yield was

not a limiting factor (marginal land). Opportunities for large animal grazing were not identified, yet

it was noted that additional expenditure for rigid solar support structures may be required for larger

animals (Macknick, 2014). This alludes to the problem facing integration with cattle grazing.

The European Bureau of Resource Economics (BRE) indicates that cattle are considered unsuitable

for co-location since they have the weight and strength to dislodge standard mounting systems

(Scurlock, 2014). Cattle cannot graze beneath panels fixed relatively low to the ground and pose

the risk of damaging infrastructure in close proximity. This challenge can be overcome by using

higher, more rigid support structures if consequent problems are resolved. Additional expenditure

may be required for robust panel support structures elevated well above the ground. A solar

developer would be required to identify an affordable type of infrastructure present in the

marketplace in appropriate quantities. Similarly, additional expenditure would be required for the

drilling and installation of such infrastructure. The soil type and presence of bedrock at a chosen

location for a cattle-integrated solar farm would therefore need to be able to support more weight

and facilitate deeper drilling. Higher panels may also require additional electrical wiring for

generated power, a cost which could compound quickly for a large scale project. Finally, general

maintenance practices would need to adapt to taller solar infrastructure. Considering these

limitations it can be said that co-location of a solar farm with a cattle grazing enterprise using

25    

current PV technology is infeasible. A solar developer that cannot afford to purchase the required

land for a solar farm should therefore consider an alternate financing strategy – solar leasing.

Solar leasing is a highly prevalent financing method available to solar developers and landowners

around the world, most commonly used in countries where multiple large-scale PV systems exist.

In Germany, for example, 11% of renewable energy capacity is effectively owned by farmers,

where land is leased to solar developers (Ferroukhi, 2015). Solar leases have been used to enhance

the value of marginal land, generate clean energy and to ensure that existing landowners retain

ownership. The advantages and disadvantages for doing so will be discussed later. First, it is

important to understand why a solar lease may be suitable for an existing landowner seeking to

develop a solar farm.

The initial capital requirements for a large scale solar project can be substantial as the resources

required can be costly – particularly those of skilled labour and materials. These resources may not

be readily available to a landowner, meaning that investment in a large scale project may not seem

feasible. For the landowner to invest in large-scale solar as an income source financial assistance

may be required. Finance provided by an investor or a commercial bank could be used to fund a

project, however, individual landowners may find it difficult to gain support from a commercial

bank which lacks experience dealing with these types of projects. Australian solar industry leaders

predict that Australian banks will eventually be comfortable with the process, yet feel that they

have “another one or two year learning curve” before they get to that point (Gifford, 2015).

Investors can therefore be used as a source of funds, an option which may not be readily available

to small private landowners. This issue gives rise to the need for an alternative financing method.

Current alternatives available to Australian landowners include national, state and local government

assistance, private grants and solar leasing programs.

A solar lease agreement is a structured finance agreement held between two or more parties which

enable landholders to install large-scale PV projects without financing the development,

construction or maintenance of the project (Clean Energy Council, 2014). A lease can be facilitated

by solar manufacturers, installers or brokers and can involve partnership with a third party that

provides credible finance. Relevant due diligence can be conducted by the facilitator of the lease to

ensure the bankability of the large-scale project and to identify the most appropriate solar

technology, project size and relevant time frames to be used. The specific terms of a lease are

tailored to individual projects on a case by case basis. Typically the relevant solar supplier is

responsible for the monitoring and maintenance of the system until the lease expires, at which point

the ownership of the project may transfer to the landholder or the supplier.

26    

Solar leases of 20-25 years are suitable to landholders who do not wish to sell their land whilst the

project is underway. The lease provides passive income for decades and secures income for

families. However, even if land is to change hands the new landholder can take advantage of the

solar lease, so long as they agree to all the relevant terms and conditions. Building on this, it can be

said that those landholders who are more willing to invest in a passive income source are those

which currently lack one. Businesses may lack passive income for a number of reasons, yet in the

case of cattle graziers it is likely that drought affected or otherwise unproductive enterprises suffer

from unstable cash flow. Intuitively this means that these landowners may be more likely to

consider a solar lease for a large-scale project. It should also be noted that landowners suffering

from poor climatic conditions are more likely to be located further west of the Great Dividing

Range where rainfall is less frequent and sunlight intensity is higher (Figure 10). Higher sunlight

intensity translates to higher solar power output yield, making the investment more attractive to

third parties and the lease more attractive to landowners.

In summary it should be acknowledged that large-scale solar projects do present opportunities for

integration with small animal enterprises as described by Macknick (2014). Even so, in the

Australian context it is likely that solar farm opportunities will need to be identified for areas that

do not use these enterprises. This chapter indicates that cattle grazing land is commonly situated in

suitable areas for solar farms, so for the purpose of this study the relationship between cattle

grazing and large-scale solar will be considered.

2.10 Concluding comments

This chapter’s critical assessment of global and national trends in the solar PV industry finds that of

the two main solar technologies, solar PV has the most potential for large-scale adoption in

Australia. Current trends in the global solar PV industry illustrate that solar PV can be used as a

major source of electricity in a developed country and it is likely that utility generation models of

the future will include more solar PV. It is established that solar leasing can facilitate this change.

In order to evaluate the suitability of a solar lease for a landowner, an analysis of hypothetical and

existing scenarios can be used. It is difficult to describe a typical solar farm, given the variations in

technology used, sunlight intensities in different locations and overall scale of a project. Thus, a

case study of a possible solar farm can be matched to the analysis of cattle grazing enterprises for

the purpose of comparison and evaluation of benefits and costs. This ex ante analysis is used to

provide land holders with economic reasoning to help determine whether a solar farm could be

used as a source of income.

27    

Chapter 3: Data Construction for Case Study

3.1 Introduction

The purpose of this chapter is to build a framework required for the ex ante analysis. A

hypothetical solar farm is described in terms of capacity, location, system selection and

corresponding minimum lease price. Typical and representative grazing enterprises for the chosen

location are also described. Finally, the chapter makes relevant assumptions necessary for the

construction of data to be used for analysis in Chapter 4.

3.2 Case study – Armidale 30MW project

For the purpose of this analysis a hypothetical solar farm is described, using data generated by

Solar Choice for the chosen solar PV system size and location (Appendix 1). System yields for this

project and associated data are used to identify a minimum lease price. In doing so, relevant

assumptions are made so that revenue streams from a 20 year solar lease may be evaluated against

revenue streams from representative and typical grazing systems for the chosen location.

A solar lease substitutes grazing activities with solar infrastructure directly, so it is important that a

large enough area of land is used to capture accurate financial performance data for varied grazing

activities and a solar system. Given that a large-scale system is described as having a capacity equal

to or greater than 1MW by the CEC, this size can be used as a minimum requirement. The land area

required to support 1MW of capacity is dependent upon the type of technology used. Solar Choice

identified polycrystalline silicon cells manufactured by Trina Solar to be readily available in the

current market and suitable for this analysis. These cells can be arranged in a fixed array and

generally require 2-3ha/MW (Gemmell, 2015). This area of grazing land is not, however, a large

enough area of land for comparison with cattle grazing systems which generally use much larger

areas of land. It is for this reason that an area of 100ha was chosen. An area this size would

facilitate a much larger 30MW project and provide relevant landholders with a more accurate

indication of potential revenue streams. Thus, using a 30MW capacity solar farm which generates

electricity for a 20 year period, a framework for analysis can be developed. Average costs and

benefits for the described grazing systems are provided by the NSW Department of Primary

Industries (DPI) on a per hectare basis, so financial data for a 100ha case study is easily calculated.

In order to obtain expected generation yields and estimate the value of this 30MW project a suitable

site is identified. As mentioned earlier, a site should be nearby transmission lines or a substation,

28    

receive adequate solar irradiance and sunlight hours, present suitable soil types to support

infrastructure and be mostly cleared. A site should also be free from shading and zoning restrictions

and have sufficient protection from flooding and fires. It is also important to consider the

opportunity cost of using land for alternative purposes. Similarly, the social importance of

preserving wildlife systems, maintaining biodiversity and reducing other negative externalities

should be considered. A suitable site which meets these criteria is identified below in Figure 11,

near Armidale, NSW.

Figure 11: Site location

Source: (ARENA, 2015)

The blue shaded area above represents approximately 250ha of land which could be suitable for a

30MW project. Given that climatic data, proximity to the 330kV substation and the topography of

land in this area is similar, the specific 100ha to be used for the solar farm will not need to be

identified. Instead, data can be simulated to estimate output yield and subsequently determine an

appropriate lease price.

29    

3.3 Grazing enterprises

When identifying suitable cattle grazing enterprises for the purpose of analysis it is useful to

consider those which are currently used and those which have previously been used for the chosen

location. Beyond this it is important to identify an enterprise which is likely to yield the greatest

returns for existing landowners, irrespective of their current enterprise choices.

Consultation with existing landowners for the selected site in Figure 11 identified multiple current

and previous enterprises. Between landholders a mixture of steer backgrounding, cow-calf

breeding, fat lamb production and small mixed grazing enterprises which rely on off-farm income

are currently used. Steer backgrounding and cow-calf breeding were identified to be the dominant

two enterprises (Foley, pers. comm, 2015). Previous landowners exhibited a similar mix of

enterprises. The major landholder for this location utilises steer backgrounding, as do a number of

neighbouring landowners. This enterprise will therefore be used to describe a typical cattle grazing

enterprise for the greater area.

Steer backgrounding refers to the grouping and acclimatisation of livestock prior to entering a

feedlot or intensive finishing system (MLA, 2015). Typically, livestock are purchased at a young

age, held for a specified period of time and then sold directly to a feedlot. In this instance steers are

purchased at 9 months of age at an average of 240kg liveweight, held for 12 months and sold

directly to a feedlot at a targeted 420kg liveweight. Expected variable costs and income for this

system are estimated using partial income statements provided by the NSW DPI. These summaries

indicate average prices and quantities relevant to inputs and outputs for the enterprise. A complete

summary of assumptions for this data is shown in Appendix 2.

In addition to the typical enterprise for the case study location an optimal enterprise is identified.

From Appendix 4 it can be seen that a similar steer backgrounding enterprise will yield the greatest

revenue for a landowner. Since it has already been established that the case study location can

support a 240-420kg steer backgrounding enterprise it can be implied that a higher profit yielding

240-460kg steer backgrounding enterprise can also be used for the subject land area. The key

differences being expenditure on pasture improvement (Appendix 2 and 3) and income from sales.

As shown by Appendix 3 the assumptions relevant to the provided partial income statement are

very similar to those used for the typical grazing enterprise. Using this information data can now be

constructed for analysis.

30    

3.4 Data construction

Before conducting an ex ante analysis consideration for the construction of data is provided. This

includes justification for the use of relevant assumptions. After vindicating the construction of data,

economic analysis is conducted.

In order to evaluate the potential financial implications of solar leasing for existing landholders a

suitable lease price for the solar farm is determined. As per traditional leasing methodology a

suitable lease price could be reached by estimating a portion of the value of land. For grazing land

in NSW the DPI recommends that a lease price of between 5-9% of the value of the land should be

used (DPI, 2007). This methodology could be used to compare the value of a solar lease to

alternative leases yet it will not be included in this analysis. Rather, consultation with Solar Choice

was used to determine an appropriate lease price so that the industry expertise and experience of

staff could be utilised. Using the data simulation shown in Appendix 1 consultation with Solar

Choice concluded that a minimum lease price of $200/ha could be used (Gemmell, 2015).

Managing Director, Angus Gemmell, suggested that a solar developer could engage with a higher

lease price, yet this would place greater pressure on profit margins. Considering the developer’s

need to negotiate a competitive Power Purchase Agreement (PPA) with a power purchaser (in this

case TransGrid) lower lease prices enable the developer to offer a lower PPA price. A lower PPA

price increases the likelihood of the power purchaser being willing to purchase electricity generated

from the solar farm (Solar Choice, 2015). Therefore in the following analysis the minimum solar

lease price of $200/ha is used.

In order to estimate the economic value of a solar farm to an existing landholder using this solar

lease a calculation of the net present value of future benefits/costs is conducted. Over the expected

20 year life span of the case study solar farm income flow is projected into the future. In doing so it

is important to indicate the real value of incomes by holding the purchasing power of money

constant relative to a specific point in time (2015). This excludes the distortionary effects of

inflation. As such, comparisons between values will be meaningful since a dollar at any given point

in time has the same purchasing power (Sinden & Thampapillai, 1995). Real values are also easier

to understand from a landowner’s perspective and are more relevant to current decisions. Using

2015 as a base time period immediate income can then be observed. For the aforementioned solar

farm $200/ha rent would be received by a landowner in the base year. Since the real value of

income is considered over the entire 20 year period the landowner will receive $200/ha for every

subsequent year. For the grazing enterprises however, the expected income to be received in 2015

is calculated. Partial income statements were provided by the DPI in 2012, so the 2012 values are

treated for three years of inflation first. This is achieved by multiplying 2012 values by Australia’s

31    

long term average rate of Consumer Price Inflation (CPI). The Reserve Bank of Australia (RBA)

indicates that since inflation targeting began in 1994 for a 2-3% range the economy’s average rate

of inflation has been 2.7% (RBA, 2015). In Appendix 6 this rate is applied to determine base year

values. Base year values are used as current real values and projected 20 years into the future just

as rent from the solar lease is.

The treatment of costs differs slightly. As per the DPI’s partial income summaries (Appendices 2

and 3) the exclusion of all fixed costs and some variable costs is useful for the purpose of analysis

to compare enterprise specific revenue streams. For grazing enterprise variable costs an average

annual rate of inflation of 2.7% is similarly used to calculate base values for 2015. This analysis

offers landholders with a reliable indication of how productive the factors of production which are

directly related to an enterprise are. This is useful because it can signal immediate changes

landowners should make to maximise profit. However, this treatment fails to consider the

additional benefit a landowner receives from a solar lease because that 100ha does not require costs

such as labour, repairs & maintenance, fuels, contracts and administration. That is to say, that it

does not indicate overall changes in net income. The relative expense required for these items can

vary. It is difficult to estimate fixed costs for an average enterprise due to variations in total land

area, levels of debt, machinery schedules, and labour used. As a consequence these costs are not

included in the initial calculation of net present values. Rather, by considering a basket of these

expenditure items as an additional benefit (income stream) for a solar lease their influence on net

present values can be accounted for. Sensitivity analysis is used to create possible scenarios where

fixed costs increase typical steer enterprise total expenditure by 10, 20 and 30%. 30% is selected as

the maximum sensitivity because an increase in costs beyond this point would see the typical

enterprise reach a breakeven point. Incremental rates of 20% and 10% are used to estimate relative

changes in net present values.

Incomes and expenses are expressed per 100ha for the purpose of this analysis, as 100ha is required

for the 30MW solar farm. Values for the DPI’s specified 240-420kg and 240-460kg steer

backgrounding enterprises are based on land areas of 97ha and 108ha respectively. In order to

ensure that exactly the same land area is used between all enterprises income and expenditure items

are adjusted proportionally to suit 100ha. It is for this reason that all values for the typical

enterprise (240-420kg steer backgrounding) are increased by 3.09% and for the optimal enterprise

(240-460kg steer backgrounding) are decreased by 7.41%. This ensures greater accuracy for results

by providing a more realistic indication of income flows for 100ha of each enterprise. Data is

standardised over the same area of land and shown in real values for the base year – 2015. Future

income and expenditure is projected 20 years into the future as shown in appendices 5, 6 and 7.

32    

Future outcomes are converted to equivalent present values using an appropriate discount rate. This

is the percentage rate of compound interest for which future benefits and costs can be adjusted to

equivalent present-day values. However, it is difficult to determine which rate should be used

because the value of future outcomes may vary between individuals. Moreover, the flow of future

outcomes for different alternatives can be exposed to varied levels of risk. It is for this reason that

three different discount rates are used to estimate the value of future outcomes. The New South

Wales Treasury recommends a central real rate of 7% should be used, including sensitivity analysis

for rates of 4% and 10% (New South Wales Treasury, 2007). These rates represent the real rate at

which future outcomes are valued which is consistent with the real values used for projections of

future income and expenditure. Net present values of future outcomes are calculated on a yearly

basis. The addition of net present values indicates the estimated value of the project to the

landowner for the 20 year period.

The net present value of an outcome at any year in the future is calculated as;

NPV = !!

(!!!)!

where ′𝐵!′ is benefit in time period  ′𝑡′ and ′𝑖′ is the discount rate

Similarly, the sum of net present values can be calculated;

NPVSUM =   !!!!! !

!

!!!

For gross margin analysis, values can be compared on a per hectare basis. In an agricultural context

a gross margin may be defined as the gross income from an enterprise minus the variable costs

incurred in achieving it. A gross margin is a useful indicator for landholders because it shows how

much revenue a business can generate from an enterprise minus the variable costs incurred in doing

so. In the context of cattle grazing enterprises this can be represented as a dollar value per hectare,

rather than as a percentage of overall revenue (as accounting generally would express a gross

margin). This is useful for the selection of the most profitable enterprise for a farm business and

can be used to determine the minimum price point to be used for the price of a solar lease. In

December 2012 the NSW DPI provided budgets for varied livestock enterprises, including cattle

enterprises shown in Appendix 2. This data is based on a 100 cow herd with a weaning rate of 86%

(NSW Department of Primary Industries, 2015). Using the Australian Bureau of Statistic’s CPI

calculator tool these values are altered to reach more accurate 2015 values (Australian Bureau of

Statistics, 2015).

33    

3.5 Concluding comments

From Chapter 3’s data construction the main parameters to be used for the following case study

analysis are: 100ha grazing land, fixed solar lease price of $200/ha for a 30MW system, 20 year

time frame, typical enterprise of steer backgrounding for 240-420kg and optimal enterprise of steer

backgrounding for 240-460kg. 2012 DPI partial income summary values are adjusted for 100ha and

inflation to reach 2015 base year values. It is assumed that this adjustment provides an accurate

reflection of 2015 cattle prices. It is also assumed that these may be treated as real values, so real

discount rates of 4, 7 and 10% are applied for consistency. Using this information analysis is

undertaken to provide results shown in Chapter 4.

34    

Chapter 4: Ex ante Analysis

4.1 Introduction

This chapter provides a summary of results for the three different scenarios. A central

discount rate of 7% estimates the net present value of each alternative and appropriate sensitivity

analysis indicates the relative influence of varied discount rates. Gross margin analysis is also used

to compare alternatives with appropriate sensitivity analysis. Both of these pieces of analysis are

used to estimate breakeven points between alternatives.

4.2 Net present values

The calculated net present value sums are summarised and presented in Table 4. Models used to

calculate these values are shown in appendices 5, 6 and 7. The choice of each discount rate can be

seen to have a significant influence on results. Each value shown in Table 4 indicates the value of

an alternative over 20 years in real dollar terms for a corresponding discount rate. The alternative

yielding the highest net present value is shown to be $362,315.66 for ‘Steers 240-260kg’ with a 4%

discount rate. Conversely, the lowest net present value is $190,271.27 for the solar lease when a

discount rate of 10% is used. An interpretation of these results and corresponding analysis is

provided in Chapter 5.

Table 4: Net present value results, 2015-2035*

Net present value for the 20 year period ($) Discount rate Solar lease Steers 240-420kg Steers 240-460kg 4% 291,806.53 310,938.19 362,315.66 7% 231,880.28 247,083.02 287,910.68 10% 190,271.27 202,746.00 236,248.24

*100ha case study

To account for the influence of fixed costs which are not measured in Table 4’s results, further

sensitivity analysis is used to price the additional expenditure items in baskets of 10, 20 and 30%

increments as additional revenue streams for the solar lease. Using the $200 lease price as a base

the additional grazing expenditure can be seen as an addition to rent revenue. Respective additions

are shown in Table 5 below. These additions are included in the model shown in Appendix 9.

35    

Table 5: Accounting for grazing fixed costs as additional revenue streams for a solar lease

Additional Expenditure Enterprise Base* 10% 20% 30% Steers 240-420kg ($) 64,475.52

(+$0/ha) 70,923.07

(+$64.47/ha) 77,370.62

(+$128.95/ha) 83,818.18

(+$193.43/ha) Steers 240-460kg ($) 58,468.31

(+$0/ha) 64,315.14

(+$58.47/ha) 70,161.97

(+$116.94/ha) 76,008.80

(+$175.40/ha) *Base year expenditure values are adjusted for 100ha

In Table 5 base values represent total expenditure for each enterprise as estimated for 2015.

Additional expenditure baskets are calculated as proportional increases in base values. Under each

value an indication of the net effect on total expenditure is illustrated on a per hectare basis. These

per hectare additions are directly added to the $200 lease price to yield new net present values

shown in Table 6. With the central real discount rate of 7% the new rent revenues are entered into

the discounting model (Appendix 9). In effect, the new values illustrate the addition of original

solar lease net present values and the benefits of saving expenditure on fixed costs. Table 6

summarises these results:

Table 6: Net present value sums, including fixed cost savings

Additional Benefit Solar Lease NPV Sum additions Base 10% 20% 30% NPV Sum*: Steers 240-420kg ($) 231,880.28 306,626.89 381,385.10 456,143.30 NPV Sum*: Steers 240-460kg ($) 231,880.28 299,670.49 367,460.69 435,239.29 *Calculated using discount rate of 7%

Alterations to the solar lease price are also used to determine the point at which rent revenue from

the lease would breakeven with each enterprise. By identifying the net present values for each steer

backgrounding enterprise at a certain point in time then solving for benefit in the corresponding

time period, this can be achieved. Calculation provided the following breakeven points:

Table 7: Breakeven lease prices

Enterprise Solar lease breakeven price ($/ha) Steers 240-420kg 213.11 Steers 240-460kg 248.33

Since real values are used for the projection of future outcomes and the same three discount rates

are applied these lease prices yield the same net present values as each corresponding enterprise for

each discount rate. Evidently, this means that the breakeven solar lease prices are equal to the 2015

gross margin per hectare rates for each grazing enterprise.

36    

4.3 Gross margin analysis

In order to compare gross margins for each cattle enterprise and the solar lease in 2015, the

provided DPI partial income statements are altered. Appendices 10 and 11 show how 2012 values

for each enterprise are first adjusted to suit an area of 100ha and then treated for average annual

inflation of 2.7% for three years. In each it can be seen that gross margins proportionally increase

over the time period. A simplified summary of each alternative’s gross margin is presented in Table

8, showing that in both cases a solar lease’s gross margin is not as competitive.

Table 8: Gross margin results

Gross margin per hectare* ($/ha) Enterprise 2012 2013 2014 2015 Growing out steers 240-420kg in 12 months 196.69 202.02 207.52 213.13 Growing out steers 240-460kg in 12 months 229.19 235.41 241.80 248.33 Solar lease - - - 200

*Gross margins quoted include pasture improvement costs

Gross margin analysis is also used to estimate the influence of a drought year on returns from each

enterprise. For a solar lease the gross margin will not change during a drought year so this value

remains unchanged. For the two steer enterprises however, gross margins can vary significantly. It

is difficult to estimate the average severity, duration and timing of a drought period, so for the

purpose of this analysis the following assumptions are made. It is assumed that drought conditions

begin when 9 month old steers are purchased (the start of the 12 month period) and that the

landholder is aware of this. Instead of spending cash on pasture improvement as shown in the DPI

summaries this cost is transferred to expenditure on hay and grain. There is no net effect on total

expenditure and livestock purchase prices are held constant. It should be noted though that in a

drought, purchase prices may change as the supply of cattle to the market increases. The critical

variable to be changed is ‘liveweight kilograms sold’, since drought conditions stress livestock and

limit weight gain. The influence of a drought is calculated by accounting for decreased liveweight

kilograms sold. Table 9 summarises the influence this has on income, using a 10% decrease in

liveweight from data in appendices 2 and 3. These results illustrate that the described drought

conditions decrease gross margins to $127/ha for the 240-420kg steer enterprise and $165.03/ha for

the 240-460kg steer enterprise. The solar lease, however, remains the same at $200/ha. The key

finding of this result is that regardless of drought conditions a solar lease can generate secure

income. Implications of this finding are discussed in the following chapter.

37    

Table 9: Comparing initial liveweight yield to drought year yield

Enterprise Income ($) Gross margin ($/ha) Normal Year Steers, 240-420kg 85,768.77 213.11 Drought Year Steers, 240-420kg 77,191.89 127.16 Normal Year Steers, 240-460kg 83,301.29 248.33 Drought Year Steers, 240-460kg 74,971.16 165.03 Normal Year Solar Lease 20,000 200.00 Drought Year Solar Lease 20,000 200.00

In contrast to drought year gross margins, grazing enterprise yield may vary due to cattle price

changes. Additional gross margin sensitivity analysis is used to account for price variations of

livestock purchased and sold. Average yearly price variations for the typical and optimal grazing

enterprises are not available, so data sets for similar steer enterprises are observed to determine

levels of price volatility. Appendix 12 shows that for a similar steer enterprise, trade steers

weighing 330-400kg, cattle prices varied between 15-20% from the period 2010-2015 (NLRS,

2015). This volatility justifies the use of sensitivity analysis to account for a 20% change in cattle

prices. Appendix 12 shows that a 20% change in prices would cause the typical steer enterprise

gross margin of $21,311.26 to increase to $28,549.66 or decrease to $14,072.89. This means that if

2015 prices are 20% greater than shown appendices 10 and 11, a typical 240-420kg steer

backgrounding enterprise may yield a 34% greater gross margin per hectare, of $285.50. Similarly,

if 2015 prices are 20% lower, the typical enterprise may yield a 51% reduced gross margin of

$140.73/ha. These findings are discussed with reference to the current cattle market in Chapter 5.

4.4 Concluding comments

In summary, the results of this study’s ex ante analysis are able to provide landholders with

economic reasoning to make enterprise decisions. It is apparent that a solar lease generates less

value than steer backgrounding enterprises when future outcomes are discounted at the same rate.

The value of a solar lease relatively increases when consideration is given to the influence fixed

costs may have on grazing enterprises. Gross margin analysis similarly finds that a solar lease

generates more value under certain circumstances – including drought. These findings are

discussed in Chapter 5 to evaluate possible implicaitons for landowners, solar developers and

governments.

38    

Chapter 5: General Discussion and Conclusions

5.1 Introduction

The purpose of this chapter is to summarise the key findings of this study and to suggest

some relevant implications for landowners, solar developers and policy makers. It provides a

landholder-centric analysis of two cattle grazing enterprises and a solar lease which determines the

intrinsic value of each alternative to the landholder over a 20 year period. This includes varied

treatments for enterprise costs and simple breakeven analysis. In addition, gross margin analysis is

used to comment on the potential for each alternative to maximise profit. Building from this

analysis consideration is given to situations where enterprise gross margins are substantially

affected. Implications of this analysis are suggested with reference to an assessment of large-scale

solar PV conducted in earlier chapters.

5.2 Overview of the study

The main objective of this case study is to conduct an ex ante analysis of the possible implications

of solar farms for Australian cattle graziers. The main research question is to determine whether it

is beneficial for these landowners to engage with large-scale solar projects using solar lease

agreements. An ex ante evaluation addresses this question using primary and secondary data to

analyse net present values and gross margins. Results from this study are considered with findings

from a literature review and assessment of solar PV in the world, Australia and agriculture through

earlier chapters.

Chapter 2 established that global energy supply will inevitably shift to renewable generation

sources. Solar PV technology was identified as an increasingly cost-competitive source of

renewable energy around the world currently used by multiple large developed economies as a

primary electricity generation source. Australia’s reliance on renewable generation sources,

however, was found to be proportionately less than the global average. In particular, solar PV

accounts for only 2.1% of national demand for electricity. 2.5% of this portion is attributable to

large scale PV. If solar is to provide for 29% of Australia’s annual electricity demands by 2050 as

the Australian Climate Council predicts, substantial changes to the current generation model are

required. An assessment of recent trends in investment, cost efficiency, development and potential

for solar PV finds that Australia’s large-scale PV sector is likely to grow rapidly over the coming

decades. The chapter concludes by identifying how and where this growth can occur – Australian

39    

grazing land. Findings from this section are used to support economic analysis in the following

chapters.

Chapter 3 builds on this assessment to construct a case study for analysis. A demonstrative model

for the development of a solar farm is built using representative cattle grazing enterprises and a

solar lease agreement. Relevant assumptions are made to approach the analysis in a landholder-

centric manner. Net present values, gross margins and associated sensitivity analysis are used to

provide economic reasoning that can help cattle graziers identify with the possible benefits of solar

leasing. Chapter 4 provides a summary of the results of this analysis which will be referred to in

this chapter’s discussion. Key findings from this study and possible implications are discussed in

the following section.

5.3 Summary and implications

5.3.1 Summary of results

Chapter 4 provides a summary of results obtained from ex ante analysis. An interpretation of results

is provided in this section so that subsequent implications can be identified. For net present value

calculations future outcomes are projected as real values using real discount rates so it can be said

that these results reflect the value of each alternative in real dollar terms.

Table 4 highlights initial net present value sums before fixed costs are accounted for. The relevant

costs and benefits shown are those which are directly related to the generation of income from each

activity. Each result contains a positive figure, so it can be said that any alternative will provide the

landowner with net gain. The alternative with the highest net present value has the highest net gain,

making it the most desirable. A preliminary interpretation of results can be conducted by observing

net present values at equivalent discount rates. The results illustrate that the optimal 240-460kg

steer backgrounding enterprise yields the greatest value for the landowner at each rate. The greatest

value - $362,315.66 is realised when this enterprise is chosen and a 4% discount rate is applied.

Similarly, at each equivalent discount rate the solar lease is the least valuable, where a discount rate

of 10% yields the lowest net present value of $190,271.27. Using these interpretations a typical

landowner has no incentive to use a solar lease. Instead, the typical landowner should seek to adopt

the heavier steer backgrounding enterprise. However, this interpretation fails to consider which

discount rate is most suitable for each alternative.

When analysing results it is important to understand the influence of each discount rate and the

basis for choosing between them. The low rate, 4%, is based on the concept of individual time

40    

preference, whilst the higher rate, 10%, is based on the concept of opportunity cost (Sinden &

Thampapillai, 1995). A higher discount rate places greater emphasis on short term outcomes and

other opportunities, since the value of future benefits decreases relatively faster. Conversely, the

lower rate reflects the value of future outcomes where an individual is indifferent between present

and future values, so should be applied when long term costs/benefits are well known. The

difference between a high rate and a low rate is therefore considered as a risk premium. When risk

is higher, a higher discount rate should be used and vice versa.

For existing landowners the relevant costs are variable and short term in nature. As such a

landowner can use values from these calculations to determine the best way to maximise short term

profit. By projecting the outcomes of a choice 20 years into the future the landowner can gauge the

suitability of a current choice if variable costs are expected to remain the same. This means that if

the landholder is unsure how variable costs will change over the 20 year period a discount rate of

7% or 10% should be observed. On the other hand, if landowners are confident that they can

predict these costs over the next 20 years the lower discount rate of 4% can be used. Even though

the cattle grazing industry is mature and relatively stable, cattle graziers are ‘price takers’ so they

are vulnerable to short-term price volatility. This makes it difficult to estimate variable

costs/benefits. For these reasons the central discount rate of 7% can be used to capture both the

influence of the industry’s stability and susceptibility to price changes. By contrast, a solar lease

agreement is contractually enforceable, meaning that a landowner can almost certainly predict

future income over a long period of time. It is for this reason that a landholder should use the net

present values indicated by a 4% discount rate to estimate the value of the solar lease. Using this

knowledge the results summarised in Table 4 can be reinterpreted.

For the central discount rate of 7% the typical 240-420kg steer enterprise yields a net present value

of $247,083.02. This indicates that the sum of future benefits generated from this enterprise over

the next 20 years is worth $247,083.00 in current dollar terms. For the optimal 240-460kg steer

enterprise the sum of future benefits is worth $287,910.68. Both of these options are worth more

than a solar lease if the 7% discount rate is applied, yielding $231,880.28. However, since returns

from the lease are nearly certain it is more appropriate to value the benefits of the solar lease using

a 4% discount rate. At this rate a 20 year solar lease is worth $291,806.53 in real dollar terms,

making it the most desirable alternative. Under these assumptions a landowner could choose to

enter a solar lease agreement to maximise net benefit. Even though this provides a good indication

of which alternative is the most profitable it does not include the effects of fixed costs. In order to

account for the influence of fixed costs which are not shared (excluded) between each alternative

further analysis is required.

41    

In situations where fixed costs increase total expenditure a landholder can consider the savings

from avoiding these costs as being equivalent to additional income received from a solar lease. This

approach is useful for landholders who are currently using one of the described steer enterprises

that are considering a solar lease. For these calculations the central real discount rate of 7% is used

to capture the risk of fixed costs changing in the long term. The real dollar value expressed through

a net present value using this approach therefore reflects the addition of actual benefit and the

implied benefit of cost reduction.

Sensitivity analysis is used to test the influence an accounting for fixed costs will have on net

present value by using increments of 10, 20 and 30% to increase total expenditure. For each test

fixed costs are considered together as a basket of costs, as shown in Table 5. Fixed costs vary for

grazing enterprises, so landholders can use Table 6 to determine which portion of fixed costs best

suits the cost structure for their enterprise. Landholders can then more accurately identify the

possible benefits of a solar lease using this information. As shown by Table 6, a landholder who is

currently using the typical 240-420kg steer backgrounding enterprise may be subject to an increase

in total expenditure by 20% when fixed costs for the 100ha are accounted for. If this is the case the

net present value of a solar lease increases to $381,385.10. This means that by accounting for fixed

costs the solar lease becomes 64.48% more valuable to the landholder. It should be borne in mind

that in reality the solar lease won’t provide additional income. Instead, the grazing enterprise is

relatively less valuable. Other results from hypothetical cost structures have notable results. In

particular, a grazier who is using the 100ha for typical 240-420kg steer backgrounding who

accounts for fixed costs through a 30% increase in total expenditure stands to gain 96.72% more

value over the 20 years using a solar lease. The net present value for a solar lease under these

circumstances is $456,143.30. Other income sources from the same 100ha may distort this

approach by making grazing enterprises relatively more profitable. Consequently this sensitivity

analysis should only be used by landholders whose enterprise suit the benefit-cost structure

described in this model.

Lease prices are also altered to determine the breakeven points between a solar lease and each

enterprise. Table 7 shows that for 240-420kg steers the breakeven price is $213.11/ha and for 240-

460kg steers the breakeven price is $248.33/ha. These values correspond to the breakeven gross

margins for each enterprise on a per hectare basis. Using the same discount rate a grazier would be

indifferent between each alternative. In reality however, the lower 4% discount rate is suited to the

solar lease and the 7% discount rate is suited to each grazing enterprise. At these rates the lease

prices required to see net present values break even with each steer backgrounding enterprise are

calculated by testing the model in Appendix 5 for the corresponding net present values. For 240-

42    

420kg steers a lease price of $169.34 would result in a net present value of $247,083.02 for each

choice. Similarly a lease price of $197.33 yields a value of $287,910.68 to breakeven with the 240-

460kg steer enterprise. Logically this implies that if grazing enterprises are discounted at a 7% rate

and the lease at a 4% rate the solar lease will always generate more value than each enterprise. A

landholder could use this information to identify solar leasing as a more valuable alternative.

In addition to discounting future outcomes from each alternative current differences between each

cattle enterprise and a solar lease can be evaluated using gross margin analysis. This analysis is

useful for an evaluation of the influence a drought will have on gross margins. Gross margin data

for 2015 is constructed in appendices 10 and 11, in order to adjust 2012 DPI values for average

annual inflation. Table 8 summarises these changes, showing that in 2015 the typical 240-420kg

steer backgrounding enterprise gross margin is $213.11/ha, the optimal 240-460kg steer

backgrounding enterprise gross margin is $248.33/ha and for the solar lease $200/ha.

Using this information a landholder can see that per hectare the optimal steer enterprise is the most

profitable, followed by the typical enterprise and then the solar lease. As discussed earlier though, a

landowner should also consider the portion of fixed costs per hectare from each grazing enterprise.

Consideration for these costs will make the solar lease seem more profitable on a per hectare basis

(Table 6). Net income per hectare is evidently a more useful measurement for landowners to

consider when evaluating the benefits of solar leasing. Even though gross margin analysis fails to

account for some costs it can be used to estimate the influence a drought and price volatility have

on each alternative.

The timing and duration of a drought and the severity of climatic conditions can vary. For this

reason it is difficult to describe a typical drought, so relevant assumptions are made. Chapter 4

outlines these assumptions, where the critical variable influenced is liveweight kilograms sold. The

DPI’s partial income summaries for each enterprise show how liveweight kilograms sold influence

sale prices, so using this information a decreased sales yield of 10% is used to estimate the

influence a drought has on gross margins per hectare. Table 9 summarises this information. For a

typical 240-420kg steer backgrounding enterprise the described drought causes a reduction in

income from sales to $77,191.89. This reduces the enterprise’s gross margin to $127.16/ha – a

67.59% reduction. For the optimal 240-420kg steer backgrounding enterprise income is reduced to

$74,971.16. The associated gross margin is $165/ha – a 50.48% reduction. For the solar lease the

gross margin of $200/ha will not change during a drought year. As such, it can be said that under

drought conditions a solar lease may generate stable income for a landowner. Moreover, by

accounting for fixed costs or considering situations where liveweight yield decreases further a solar

lease’s income may seem relatively more desirable. This highlights a potential advantage of using a

43    

solar lease. A solar lease can provide a low-risk income source to landowners irrespective of

climatic conditions. It is likely that over a 20 year period the existing landowners will experience

multiple droughts so this information is particularly relevant to current enterprise choices.

Conversely to the influence of a drought, Chapter 4’s sensitivity analysis illustrates that cattle price

volatility can significantly increase gross margins. A 20% increase in the price of cattle may lead to

a 34% increase in the typical steer enterprise’s gross margin (Appendix 12). In this situation the

value of a solar lease markedly decreases for the landowner. The 2015 330-400kg steer market

prices illustrate that current market prices are higher than those shown in appendices 10 and 11

(NLRS, 2015). Therefore, it is possible that previous analysis understates actual 2015 cattle prices.

Whilst the current prices may overstate actual values it is useful to consider the influence a 20%

decrease in prices has – which could lead to the typical enterprise gross margin decreasing by 51%.

As such, landowners should undertake enterprise decision making with the most accurate data

available.

The most significant findings of this analysis are that a solar lease can provide a secure income

source for cattle graziers for long periods of time and that in certain situations a solar lease can also

generate more income. Consequently, a low discount rate can be used to estimate the value of

future benefits and landowners can use a solar lease as a low-risk income source to avoid losses

during drought. Additionally, a minimum lease price of $200/ha can generate more value than both

typical and optimal cattle grazing enterprises under certain circumstances.

Under circumstances where fixed costs increase total expenditure by 10% for each enterprise a

$200/ha solar lease presents more value for the 20 year period for equivalent discount rates.

Compounding this information with the knowledge that a lower 4% rate is best suited to a solar

lease it can be said that a solar lease is very likely to generate more value for landowners in the

long term. The implications of these findings are discussed in the following section.

5.3.2 Implications

The implications of these results vary for landowners, solar developers, policymakers and society.

Landowners can use this study to identify whether their location is suitable for a solar farm. If land

is suitable they can evaluate the possible opportunity of engaging with a solar lease agreement on a

per hectare basis. This study describes the typical and optimal enterprises as steer backgrounding

for two different weight classes using information provided by the DPI. As shown in Appendix 4

these two enterprises yield greater gross margins per 100 hectares than most other listed

44    

enterprises. Therefore it can be implied that for most other listed enterprises solar leasing can be

used by a landowner to generate relatively more value than what is shown in this study.

Furthermore, enterprises which are not considered in the DPI summary can use this analysis to

evaluate the potential implications of solar leasing by comparing the lease model used in this

analysis to their enterprise benefit/cost structure. Regardless of a landholder’s existing enterprise no

establishment costs are required and the landholder can be relatively certain of future returns once a

lease price is negotiated.

It is difficult to value the social benefits provided by the 30MW solar farm. Even still, a landholder

can view a solar lease as a socially beneficial alternative which reduces carbon emissions and

generates electricity for households that utilises a renewable resource at little or no social or private

cost. The hypothetical 30MW solar farm described in this study is estimated to be able to produce

51,893MWh of electricity annually (Appendix 1). The DPI has advised that 1.37kg of CO2

emissions are produced for every kilowatt hour of electricity, using a 2013 generation model (DPI,

2013). Therefore the described 30MW solar farm could save up to 71,093.41 tonnes of CO2

emissions annually. The 51,893MWh of electricity produced annually should also be able to power

8,160 Australian homes. Evidently, society benefits significantly for every 30MW of solar PV

generation. Solar developers and landowners may consider this information to estimate the

additional social value of developing a solar farm. With reference to the ARENA/Ipsos social

acceptance report, a landowner may also derive benefit from the knowledge that he/she is helping

the community adopt renewable energy. Whilst these benefits are difficult to price they are

important to acknowledge for a landholder considering a solar lease.

A solar developer can use this study to gain a better understanding of the way in which a landholder

will seek to maximise returns from land using a variety of enterprises. This knowledge can be used

when negotiating a solar lease to calculate a fair price which creates value for the landholder and

allows the developer to engage with a competitive PPA. Furthermore, landholders who become

aware of the possible benefits of solar leasing described in this report may identify themselves to

solar developers as having land which could potentially be used for a solar farm. This can reduce

the expense a solar developer incurs in identifying possible locations and could create opportunities

for business growth.

The findings of this paper can also be used to recommend opportunities for governments to assist

with the development of large-scale solar PV. Chapter 2’s assessment of large-scale PV in

Australia can be used to highlight the potential for growth in the sector. It should be noted that

other developed economies have been able to adopt solar PV as a primary energy source and that

Australia will inevitably need to change its energy generation mix. Solar energy is identified as an

45    

increasingly cost-competitive source of electricity with significant potential to meet Australia’s

electricity demands. It is also apparent that the development of large scale PV projects will require

large areas of land in suitable locations, establishing the need to research ways such projects can be

integrated or substituted with existing enterprises. It is for these reasons that funding for solar PV

research may be required to identify the most effective ways to integrate or substitute solar farms

with existing enterprises. For this study though, recommendations are made to suggest how policy

makers can assist with the development of solar farms using solar leasing agreements. To be

consistent with earlier analysis, recommendations are made with consideration for the additional

benefits a landholder could derive from government support.

Government support via subsidies or competitive funding programs could be used to encourage

landholders to use their land for solar farming. Solar developers are currently challenged by the

difficulty of selecting a suitable location and negotiating agreements with landholders. Subsidy

support could provide a financial incentive for existing landholders to identify their enterprises as

having potential to utilise solar leasing.

An example of how a subsidy could be used in such a way can be derived from the results shown in

Tables 6 and 7. This piece of analysis accounted for additional expenditure on fixed cost items as

baskets of costs that increased total expenditure by 10, 20 and 30%. Just as analysis considered

these as additional benefits of solar leasing they can also be considered to estimate the value that

could be created by a subsidy. For instance, if a landowner was paid a $64.47/ha subsidy for

undertaking solar leasing the effective rent revenue earned from the lease could be $264.47/ha,

assuming the original $200/ha lease price. If the subsidy was in place for the duration of the lease

and a 100ha project was used, the resulting net present value would be $306,626.89 (Table 7).

Therefore by providing $6,647 annually through a subsidy the solar lease creates 32% more value

for the landowner. This may increase the likelihood of existing landowners approaching solar

developers to consider lease agreements for solar farms. A similar subsidy could be used to provide

solar developers with a financial incentive to develop solar farms. Benefit could be transferred to

the developer by providing $64.47/ha of solar farm installed. This would assist the negotiation of a

fair lease price between each party, where benefit could still be passed on to the landholder through

a higher lease price. This example illustrates that a relatively inexpensive subsidy could be used to

create significantly more value for existing landowners and developers.

A number of other means may be used to provide support for large-scale PV. However, additional

research may be required to evaluate the potential usefulness of varied support programs. For this

study a subsidy is shown to be a simple, cost-effective way to create value for landholders and solar

developers.

46    

5.4 Areas for further analysis

This analysis is structured in a landholder-centric manner so that the potential implications of solar

farms for Australian cattle graziers can be evaluated. An assessment of large-scale solar PV in

Australia reviews existing secondary data and case study analysis provides an evaluation of one

particular opportunity – a solar lease. As such there are a number of opportunities for further

analysis. Before suggesting additional opportunities the limitations of this paper are mentioned. For

the purpose of analysis a number of assumptions had to be made for data construction. Some of

these assumptions present research limitations, which may require additional research to be

undertaken.

A hypothetical solar farm is described using solar PV technology that is currently available in the

marketplace. The capacity of the solar farm is representative of a typical large-scale project and a

possible location is identified. Further study could be used to test the system yields possible for

other large-scale solar technologies such as CSP. Similarly, other locations could be used to test the

value of a solar farm to different grazing enterprises. The $200/ha lease price was provided by

Solar Choice, so additional developers could be approached for alternate pricing information. In

total, additional research could be used to test the potential implications of large-scale solar using a

different technology, location, capacity and pricing model. Similarly, it may be useful to research

the potential for co-locating cattle grazing enterprises with large-scale solar systems.

For the chosen grazing enterprises and associated financial information a number of limitations

exist. Partial income summaries use information from 2012 and fail to account for all costs relevant

to the land area used. Considering current increases in cattle market prices it is very likely that this

study understates the profitability of each grazing enterprise. More recent data that incorporates

current prices and all fixed costs for each enterprise could be used for further analysis to evaluate

the implications of solar leasing for graziers. Further analysis could also be used to test the value of

a solar lease against varied agricultural enterprises such as cropping, sheep and free-range poultry.

Regardless of the topic for future study though, the findings of this paper can be used to show

relative differences in value using a landholder-centric ex ante analysis.

5.5 Concluding comments

This paper builds on existing research to determine current and expected trends for the solar PV

industry. It was found that Australia’s uptake of large-scale solar lags behind the global average

uptake and that it will be necessary for this to change. There is significant growth potential for solar

47    

farms in Australia and it is very likely that cattle grazing land can accommodate their development.

Cattle grazing cannot, however, be integrated with large-scale solar under a co-location model

because current solar technology is not suitable for interaction with large animals. Instead, solar

leasing was identified as the most suitable way to develop solar farms on grazing land using current

solar PV technology. It was found that landholders can create value in the short and long term using

solar leasing, in the majority of circumstances. Analysis showed that solar leasing can provide a

secure income source for graziers. This is particularly desirable when the influences of drought

conditions on income are considered. Case study results illustrate that if Australian governments

are to support the growth of large-scale solar PV, inexpensive leasing subsidies can be used to

create significant benefits for landowners and developers. This paper may be used to identify the

potential for private and societal value creation through large-scale solar PV.

48    

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51    

Appendices

Appendix 1: Solar Choice 30MW solar farm output

52    

Appendix 1

53    

Appendix 1

54    

88 Steers @ $785 /hd 10 Steers @ $769 /hd

A. Total Income:

VARIABLE COSTS:

$69,115 $7,686

 $76,801

 

   

Steer Purchase 100 steers purchased at $444 /hd $44,400 Cartage to Property 100 steers at $10.00 /head $1,000 Livestock and vet costs: see section titled beef health costs for details. $926 Other costs $0 Fodder crops - 12 ha per 100 steers $1,800 Hay & Grain $0 Droughts can increase feed costs. For example costs see main menu. $0 Pasture maintenence 97 ha improved pasture) $4,850 Livestock selling cost (see assumptions on next page) $4,746   $57,722

GM pasture

$23,929 $239.29

$31.00 $246.69

 

 

Appendix 2: DPI partial income summary (steers 240-420kg)

BEEF CATTLE GROSS MARGIN BUDGET

 Farm enterprise Budget Series: December 2012

 Enterprise: Growing out steers for feedlot market 240kg-420kg in 12 months

   

Enterprise Unit: 100 steers  

Pasture: Improved pasture

     Standard Your

INCOME: Budget Budget                                          

B. Total Variable Costs:  GM including pasture cost

GROSS MARGIN (A-B) $19,079 GROSS MARGIN/STEER $190.79 GROSS MARGIN/DSE* $24.71 GROSS MARGIN/HA $196.69

 Change in gross margin ($/steer) for change in price &/or the weight of sale stock

 Liveweight (kg's) of Stock sold

Steer sale price cents/kg live 167 177 187 197 207

Steer wt.          -40 kgs 380 -20 kgs 400

0 420 +20 kgs 440

48 84 120 156 193 80 118 155 193 231

112 151 191 230 270 143 185 226 267 309

 

Change in gross margin ($/steer) for change in purchase price & sale price.  

Steer sale price cents/kg live Steer Purchase Price C/Kg

167 177 187 197 207

165 175 185 195

159 199 239 279 318 135 175 215 255 294 111 151 191 231 270 87 127 167 207 246

55    

90% steers sold at 21 months 420 kg @187c/kg live weight 10% steers sold at 21 months urchases Steers purchased at 9 months  Steers kept for 12 months

420 kg  

240 kg

@183c/kg  @185c/kg

live weight

live weight

 

Appendix 2 Assumptions Growing out steers for feedlot market 240kg-420kg in 12 months  

Enterprise unit is 100 steers purchased at 9 months of age at 240kg liveweight, held for 12 months and turned off at 420 kg liveweight direct to feedlot.

   

Sales    

P          

Selling costs include: Commission 3.5%, yard dues $0 (sold direct to feedlot.) MLA levy $5/hd, average freight cost to feedlot $16.00/hd, no NLIS tags costed in this budget.

   

Mortality rate of adult stock: 2%  

   

The average feed requirement for this enterprise is rated at 1.16 LSU 7.97 dse's*. This is an average figure and will vary during the year.

       

Note that as with breeding enterprises there has been no interest charged on livestock. If an interest charge @ 10.0%p.a. for 365 days is charged a further $4,440 should be allowed in the budget.  

Marketing Information: Suited as feeder steers for the premium Japanese 200 days + on feed market. Most common turnoff weights 380kg - 460kg liveweight. Care is needed in purchasing the right type of cattle which are likely to be at the higher value end of the market. This is a specialised operation. Freight costs will vary depending on proximity to major feedlots.

             

Production Information: Breeds preferred Murray Grey, Angus, Shorthorn or Wagyu/British crosses when available. Liveweight scales on farm are essential. Growing out enterprises can be risky because of the price variation in both purchases and sales. Producers should consult the table on the previous page that shows gross margin changes due to variation in purchase and sale prices. Producers should determine the maximum purchase price they are prepared to pay before the sale. Liveweight and description buying are recommended methods.

       

NSW Department of Industry and Investment. Farm Enterprise Budget Series

56    

88 Steers @ $851 /hd 10 Steers @ $815 /hd

 A. Total

 VARIABLE COSTS:

 

 

   

Steer Purchase 100 steers purchased at $444 /hd $44,400 Cartage to Property 100 steers at $10.00 /head $1,000 Livestock and vet costs: see section titled beef health costs for details. $926 Other costs $0 Fodder crops (12 ha) $1,800 Hay & Grain or silage $0 Droughts can increase feed costs. For example costs see main menu. $0 Pasture maintenence (for 108 ha of improved country) $5,400 Livestock selling cost (see assumptions on next page) $4,754    

 $58,280

 GM excluding pasture cost

 

 

Appendix 3: DPI partial income summary (steers 240-460kg)

 BEEF CATTLE GROSS MARGIN BUDGET Farm enterprise Budget Series: December 2012 Enterprise: Growing out steers 240kg - 460kg in 12 months Enterprise Unit: 100 steers

 Pasture: Improved Pasture

               Standard Your

INCOME: Budget Budget                                        

B. Total Variable Costs:  

GM including pasture cost

GROSS MARGIN (A-B) $24,753 GROSS MARGIN/STEER $247.53 GROSS MARGIN/DSE* $28.68 GROSS MARGIN/HA $229.19

 Change in gross margin ($/steer) for change in price &/or the weight of sale stock

 

Liveweight (kg's) of Stock sold

Steer sale price cents/kg live 165 175 185 195 205

Steer wt.            

-20 kgs 440 0 460

+20 kgs 480

         129 171 213 254 296 161 204 248 291 334 192 237 282 327 372

 

Change in gross margin ($/steer) for change in purchase price & sale price.  

Steer sale price cents/kg live Steer Purchase Price C/Kg

165 175 185 195 205

165 175 185 195 205

209 252 296 339 382 185 228 272 315 358 161 204 248 291 334 137 180 224 267 310 113 156 200 243 286

57    

Appendix 3 Assumptions Growing out steers 240kg - 460kg in 12 months  Enterprise unit is 100 steers purchased at 9 months of age at 240kg liveweight, held for 12 months and sold direct to feedlots at 460kg liveweight.

   Sales

90% steers sold at 21 months 460 kg @185c/kg live weight 10% steers sold at 21 months 450 kg @181c/kg live weight

Purchases Steers purchased at 9 months 240 kg @185c/kg live weight

 Steers kept for 12 months

         Selling costs include: Commission 3.5%, yard dues $0 (sold direct to feedlot.)

MLA levy $50/hd, average freight cost to feedlot16.00/hd, no NLIS tags costed in this budget.

   Mortality rate of adult stock: 2%  The average feed requirement for this enterprise is rated at 1.29 LSU 8.90 dse's*. This is an average figure and will vary during the year.

       Note that as with breeding enterprises there has been no interest charged on livestock. If an interest charge of 10% pa is charged a further $4440 of costs should be allowed in the budget. Marketing Information: Finished animals are best marketed in deck loads of straight lines, so care needs to be taken when purchasing stores to ensure an even line of weaners for weight and frame. Later maturing types prefered for the Japanese feedlot 120-150 day grain fed market. Some could be taken through to the Korean/EU market. Freight costs will vary depending on proximity to major feedlots.

   Production Information: An increasingly common option in the Riverina and North West of NSW. There will generally be a need to finish the weaning process of stores after purchase which requires adequate facilities on farm. Growing out enterprises can be risky because of the price variation in both purchases and sales. Producers should consult the table on the previous page that shows gross margin changes due to variation in purchase and sale prices. Producers should determine the maximum purchase price they are prepared to pay before the sale. Liveweight and description buying are recommended methods.

      NSW Department of Industry and Investment. Farm Enterprise Budget Series

58    

Appendix 4: DPI gross margin summaries

 

 Summary of gross margins for NSW beef enterprises, December 2012

     

Enterprise    

DSE Rating

 No of

hectares

   GM/cow or / head

 

 GM/ha

 

 GM/DSE

 

 GM/LSU

imp nat    Inland Weaners  North Coastal Weaners 1  North Coastal Weaners 2  Specialist local trade  Local trade/feeders (creep fed) Yearling production (southern/central NSW) Young cattle 15 - 20 mths  Young cattle heavy feeder steers Growing out early weaned calves 160-340kg in 12 months Growing out steers 240-420kg in 12 months. Growing out steers 240-460kg in 12 months  

EU Cattle  Japanese Ox (grassfed)

   

15.25  

13.39  

16.49  

15.84  

16.57  

17.91 18.96

 17.16

 6.35

 7.97

 8.9

 23.66

 22.84

           

173  

209  

203  

211 80

       

80  

97  

108  

295  

92

   

372  

254                  

306  

424                    

400

$*  

281.01  

119.25  

218.96  

274.59  

300.11  

347.35 434.66

 427.18

 165.68

 190.79

 247.53

 513.94

 539.81

$*  

75.54  

46.95  

126.57  

131.38  

147.84  

164.62 112.61

 100.75

 207.11

 196.69

 229.19

 174.22

 109.72

$*  

18.89  

11.76  

15.84  

16.46  

18.45  

20.57 23.34

 25.22

 26.01

 24.71

 28.68

 21.81

 23.12

$*  

130.31  

81.15  

109.32  

113.59  

127.27  

141.90 161.07

 174.00

 179.47

 170.53

 197.91

 150.52

 159.51

   

*Gross Margins quoted include pasture costs. Individual budgets also report gross margins without pasture costs.

                           

NSW Department of Industry and Investment. Farm Enterprise Budget Series

59    

Appendix 5: Net present values – Solar

2015 2016 2017 2018 2019 2020 2021 Year 0 1 2 3 4 5 6 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Net Present Values NPV/year (7%) 20,000 18,692 17,469 16,326 15,258 14,260 13,327

NPV/year (4%) 20,000 19,231 18,491 17,780 17,096 16,439 15,806 NPV/year (10%) 20,000 18,182 16,529 15,026 13,660 12,418 11,289

2022 2023 2024 2025 2026 2027 2028 Year 7 8 9 10 11 12 13 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Net Present Values NPV/year (7%) 12,455 11,640 10,879 10,167 9,502 8,880 8,299 NPV/year (4%) 15,198 14,614 14,052 13,511 12,992 12,492 12,011 NPV/year (10%) 10,263 9,330 8,482 7,711 7,010 6,373 5,793

2029 2030 2031 2032 2033 2034 2035 Year 14 15 16 17 18 19 20 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Net Present Values NPV/year (7%) 7,756 7,249 6,775 6,331 5,917 5,530 5,168 NPV/year (4%) 11,550 11,105 10,678 10,267 9,873 9,493 9,128 NPV/year (10%) 5,267 4,788 4,353 3,957 3,597 3,270 2,973

NPV Sums NPV Sum (7%) 231,880.28 NPV Sum (4%) 291,806.53 NPV Sum (10%) 190,271.27

60    

Appendix 6: Net present values – (steers 240-420kg)

2012 2013 2014 2015 2016 2017 2018 Year 0 1 2 3 Income Sales: 90% of steers 71,251 73,181 75,165 77,202 77,202 77,202 77,202 Sales: 10% of steers 7,923 8,138 8,359 8,585 8,585 8,585 8,585 Total Income 79,174 81,320 83,523 85,787 85,787 85,787 85,787 Expenditure Steer purchase 45,772 47,012 48,286 49,595 49,595 49,595 49,595 Cartage to property 1,031 1,059 1,088 1,117 1,117 1,117 1,117 Livestock & vet cost 955 980 1,007 1,034 1,034 1,034 1,034 Other costs - - - - - - - Fodder crops 1,856 1,906 1,958 2,011 2,011 2,011 2,011 Hay & grain - - - - - - - Pasture maintenance 5,000 5,135 5,275 5,417 5,417 5,417 5,417 Livestock selling cost 4,893 5,025 5,161 5,301 5,301 5,301 5,301 Total Expenditure 59,506 61,118 62,774 64,476 64,476 64,476 64,476 Net Benefit/Cost 19,669 20,202 20,749 21,311 21,311 21,311 21,311 Net Present Values NPV/year (7%) 21,311 19,917 18,614 17,396

NPV/year (4%) 21,311 20,492 19,703 18,946 NPV/year (10%) 21,311 19,374 17,613 16,011

2019 2020 2021 2022 2023 2024 2025 Year 4 5 6 7 8 9 10 Income Sales: 90% of steers 77,202 77,202 77,202 77,202 77,202 77,202 77,202 Sales: 10% of steers 8,585 8,585 8,585 8,585 8,585 8,585 8,585 Total Income 85,787 85,787 85,787 85,787 85,787 85,787 85,787 Expenditure Steer purchase 49,595 49,595 49,595 49,595 49,595 49,595 49,595 Cartage to property 1,117 1,117 1,117 1,117 1,117 1,117 1,117 Livestock & vet cost 1,034 1,034 1,034 1,034 1,034 1,034 1,034 Other costs - - - - - - - Fodder crops 2,011 2,011 2,011 2,011 2,011 2,011 2,011 Hay & grain - - - - - - - Pasture maintenance 5,417 5,417 5,417 5,417 5,417 5,417 5,417 Livestock selling cost 5,301 5,301 5,301 5,301 5,301 5,301 5,301 Total Expenditure 64,476 64,476 64,476 64,476 64,476 64,476 64,476 Net Benefit/Cost 21,311 21,311 21,311 21,311 21,311 21,311 21,311 Net Present Values NPV/year (7%) 16,258 15,195 14,201 13,272 12,403 11,592 10,834

NPV/year (4%) 18,217 17,516 16,843 16,195 15,572 14,973 14,397 NPV/year (10%) 14,556 13,233 12,030 10,936 9,942 9,038 8,216

61    

Appendix 6

2026 2027 2028 2029 2030 2031 2032 Year 11 12 13 14 15 16 17 Income Sales: 90% of steers 77,202 77,202 77,202 77,202 77,202 77,202 77,202 Sales: 10% of steers 8,585 8,585 8,585 8,585 8,585 8,585 8,585 Total Income 85,787 85,787 85,787 85,787 85,787 85,787 85,787 Expenditure Steer purchase 49,595 49,595 49,595 49,595 49,595 49,595 49,595 Cartage to property 1,117 1,117 1,117 1,117 1,117 1,117 1,117 Livestock & vet cost 1,034 1,034 1,034 1,034 1,034 1,034 1,034 Other costs - - - - - - - Fodder crops 2,011 2,011 2,011 2,011 2,011 2,011 2,011 Hay & grain - - - - - - - Pasture maintenance 5,417 5,417 5,417 5,417 5,417 5,417 5,417 Livestock selling cost 5,301 5,301 5,301 5,301 5,301 5,301 5,301 Total Expenditure 64,476 64,476 64,476 64,476 64,476 64,476 64,476 Net Benefit/Cost 21,311 21,311 21,311 21,311 21,311 21,311 21,311 Net Present Values NPV/year (7%) 10,125 9,462 8,843 8,265 7,724 7,219 6,747

NPV/year (4%) 13,843 13,311 12,799 12,307 11,833 11,378 10,941 NPV/year (10%) 7,469 6,790 6,173 5,612 5,102 4,638 4,216

NPV Sums NPV Sum (7%) 247,083.02 NPV Sum (4%) 310,938.19 NPV Sum (10%) 202,746.00

2033 2034 2035 Year 18 19 20 Income Sales: 90% of steers 77,202 77,202 77,202 Sales: 10% of steers 8,585 8,585 8,585 Total Income 85,787 85,787 85,787 Expenditure Steer purchase 49,595 49,595 49,595 Cartage to property 1,117 1,117 1,117 Livestock & vet cost 1,034 1,034 1,034 Other costs - - - Fodder crops 2,011 2,011 2,011 Hay & grain - - - Pasture maintenance 5,417 5,417 5,417 Livestock selling cost 5,301 5,301 5,301 Total Expenditure 64,476 64,476 64,476 Net Benefit/Cost 21,311 21,311 21,311 Net Present Values NPV/year (7%) 6,305 5,893 5,507

NPV/year (4%) 10,520 10,115 9,726 NPV/year (10%) 3,833 3,485 3,168

62    

Appendix 7: Net present values – (steers 240-460kg)

2012 2013 2014 2015 2016 2017 2018 Year 0 1 2 3 Income Sales: 90% of steers 69,339 71,218 73,148 75,130 75,130 75,130 75,130 Sales: 10% of steers 7,541 7,746 7,956 8,171 8,171 8,171 8,171 Total Income 76,880 78,964 81,103 83,301 83,301 83,301 83,301 Expenditure Steer purchase 41,110 42,224 43,368 44,543 44,543 44,543 44,543 Cartage to property 926 951 977 1,003 1,003 1,003 1,003 Livestock & vet cost 857 881 904 929 929 929 929 Other costs - - - - - - - Fodder crops 1,667 1,712 1,758 1,806 1,806 1,806 1,806 Hay & grain - - - - - - - Pasture maintenance 5,000 5,135 5,275 5,417 5,417 5,417 5,417 Livestock selling cost 4,402 4,521 4,644 4,769 4,769 4,769 4,769 Total Expenditure 53,961 55,424 56,926 58,468 58,468 58,468 58,468 Net Benefit/Cost 22,919 23,540 24,178 24,833 24,833 24,833 24,833 Net Present Values NPV/year (7%) 24,833 23,208 21,690 20,271

NPV/year (4%) 24,833 23,878 22,959 22,076 NPV/year (10%) 24,833 22,575 20,523 18,657

2019 2020 2021 2022 2023 2024 2025 Year 4 5 6 7 8 9 10 Income Sales: 90% of steers 75,130 75,130 75,130 75,130 75,130 75,130 75,130 Sales: 10% of steers 8,171 8,171 8,171 8,171 8,171 8,171 8,171 Total Income 83,301 83,301 83,301 83,301 83,301 83,301 83,301 Expenditure Steer purchase 44,543 44,543 44,543 44,543 44,543 44,543 44,543 Cartage to property 1,003 1,003 1,003 1,003 1,003 1,003 1,003 Livestock & vet cost 929 929 929 929 929 929 929 Other costs - - - - - - - Fodder crops 1,806 1,806 1,806 1,806 1,806 1,806 1,806 Hay & grain - - - - - - - Pasture maintenance 5,417 5,417 5,417 5,417 5,417 5,417 5,417 Livestock selling cost 4,769 4,769 4,769 4,769 4,769 4,769 4,769 Total Expenditure 58,468 58,468 58,468 58,468 58,468 58,468 58,468 Net Benefit/Cost 24,833 24,833 24,833 24,833 24,833 24,833 24,833 Net Present Values NPV/year (7%) 18,945 17,706 16,547 15,465 14,453 13,507 12,624

NPV/year (4%) 21,227 20,411 19,626 18,871 18,145 17,447 16,776 NPV/year (10%) 16,961 15,419 14,018 12,743 11,585 10,532 9,574

63    

Appendix 7

2026 2027 2028 2029 2030 2031 2032 Year 11 12 13 14 15 16 17 Income Sales: 90% of steers 75,130 75,130 75,130 75,130 75,130 75,130 75,130 Sales: 10% of steers 8,171 8,171 8,171 8,171 8,171 8,171 8,171 Total Income 83,301 83,301 83,301 83,301 83,301 83,301 83,301 Expenditure Steer purchase 44,543 44,543 44,543 44,543 44,543 44,543 44,543 Cartage to property 1,003 1,003 1,003 1,003 1,003 1,003 1,003 Livestock & vet cost 929 929 929 929 929 929 929 Other costs - - - - - - - Fodder crops 1,806 1,806 1,806 1,806 1,806 1,806 1,806 Hay & grain - - - - - - - Pasture maintenance 5,417 5,417 5,417 5,417 5,417 5,417 5,417 Livestock selling cost 4,769 4,769 4,769 4,769 4,769 4,769 4,769 Total Expenditure 58,468 58,468 58,468 58,468 58,468 58,468 58,468 Net Benefit/Cost 24,833 24,833 24,833 24,833 24,833 24,833 24,833 Net Present Values NPV/year (7%) 11,798 11,026 10,305 9,631 9,001 8,412 7,861

NPV/year (4%) 16,131 15,511 14,914 14,340 13,789 13,259 12,749 NPV/year (10%) 8,704 7,913 7,193 6,539 5,945 5,404 4,913

2033 2034 2035 Year 18 19 20 Income Sales: 90% of steers 75,130 75,130 75,130 Sales: 10% of steers 8,171 8,171 8,171 Total Income 83,301 83,301 83,301 Expenditure Steer purchase 44,543 44,543 44,543 Cartage to property 1,003 1,003 1,003 Livestock & vet cost 929 929 929 Other costs 1 2 3 Fodder crops 1,806 1,806 1,806 Hay & grain 1 2 3 Pasture maintenance 5,417 5,417 5,417 Livestock selling cost 4,769 4,769 4,769 Total Expenditure 58,470 58,472 58,474 Net Benefit/Cost 24,831 24,829 24,827 Net Present Values NPV/year (7%) 7,347 6,865 6,416

NPV/year (4%) 12,257 11,785 11,331 NPV/year (10%) 4,466 4,060 3,690

NPV Sums NPV Sum (7%) 287,910.68 NPV Sum (4%) 362,315.66 NPV Sum (10%) 236,248.24

64    

Appendix 8: Breakeven analysis

65    

Appendix 9: Sensitivity, net present values – Solar

2015 2016 2017 2018 2019 2020 2021 Year 0 1 2 3 4 5 6 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Sensitivity Rent & Incomes

Steers, 240-420kg: 10% increase

264 264 264 264 264 264 264

Total Income 26,447 26,447 26,447 26,447 26,447 26,447 26,447 Steers, 240-420kg:

20% increase 329 329 329 329 329 329 329

Total Income 32,895 32,895 32,895 32,895 32,895 32,895 32,895 Steers, 240-420kg:

30% increase 393 393 393 393 393 393 393

Total Income 39,343 39,343 39,343 39,343 39,343 39,343 39,343 Steers, 240-460kg:

10% increase 258 258 258 258 258 258 258

Total Income 25,847 25,847 25,847 25,847 25,847 25,847 25,847 Steers, 240-460kg:

20% increase 317 317 317 317 317 317 317

Total Income 31,694 31,694 31,694 31,694 31,694 31,694 31,694 Steers, 240-460kg:

30% increase 375 375 375 375 375 375 375

Total Income 37,540 37,540 37,540 37,540 37,540 37,540 37,540 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost (Base) 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Steers, 240-420kg:

10% increase 26,447 26,447 26,447 26,447 26,447 26,447 26,447

Steers, 240-420kg: 20% increase

32,895 32,895 32,895 32,895 32,895 32,895 32,895

Steers, 240-420kg: 30% increase

39,343 39,343 39,343 39,343 39,343 39,343 39,343

Steers, 240-460kg: 10% increase

25,847 25,847 25,847 25,847 25,847 25,847 25,847

Steers, 240-460kg: 20% increase

31,694 31,694 31,694 31,694 31,694 31,694 31,694

Steers, 240-460kg: 30% increase

37,540 37,540 37,540 37,540 37,540 37,540 37,540

NPV ( i = 7%) (Base) 20,000 18,692 17,469 16,326 15,258 14,260 13,327

Steers, 240-420kg: 10% increase

26,447 24,717 23,100 21,589 20,176 18,856 17,623

Steers, 240-420kg: 20% increase

32,895 30,743 28,732 26,852 25,095 23,454 21,919

Steers, 240-420kg: 30% increase

39,343 36,769 34,364 32,116 30,015 28,051 26,216

Steers, 240-460kg: 10% increase

25,847 24,156 22,576 21,099 19,719 18,429 17,223

Steers, 240-460kg: 20% increase

31,694 29,621 27,683 25,872 24,179 22,597 21,119

Steers, 240-460kg: 30% increase

37,540 35,084 32,789 30,644 28,639 26,766 25,014

66    

Appendix 9

2022 2023 2024 2025 2026 2027 2028 Year 7 8 9 10 11 12 13 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Sensitivity Rent & Incomes

Steers, 240-420kg: 10% increase

264 264 264 264 264 264 264

Total Income 26,447 26,447 26,447 26,447 26,447 26,447 26,447 Steers, 240-420kg:

20% increase 329 329 329 329 329 329 329

Total Income 32,895 32,895 32,895 32,895 32,895 32,895 32,895 Steers, 240-420kg:

30% increase 393 393 393 393 393 393 393

Total Income 39,343 39,343 39,343 39,343 39,343 39,343 39,343 Steers, 240-460kg:

10% increase 258 258 258 258 258 258 258

Total Income 25,847 25,847 25,847 25,847 25,847 25,847 25,847 Steers, 240-460kg:

20% increase 317 317 317 317 317 317 317

Total Income 31,694 31,694 31,694 31,694 31,694 31,694 31,694 Steers, 240-460kg:

30% increase 375 375 375 375 375 375 375

Total Income 37,540 37,540 37,540 37,540 37,540 37,540 37,540 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost (Base) 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Steers, 240-420kg:

10% increase 26,447 26,447 26,447 26,447 26,447 26,447 26,447

Steers, 240-420kg: 20% increase

32,895 32,895 32,895 32,895 32,895 32,895 32,895

Steers, 240-420kg: 30% increase

39,343 39,343 39,343 39,343 39,343 39,343 39,343

Steers, 240-460kg: 10% increase

25,847 25,847 25,847 25,847 25,847 25,847 25,847

Steers, 240-460kg: 20% increase

31,694 31,694 31,694 31,694 31,694 31,694 31,694

Steers, 240-460kg: 30% increase

37,540 37,540 37,540 37,540 37,540 37,540 37,540

NPV ( i = 7%) (Base) 12,455 11,640 10,879 10,167 9,502 8,880 8,299

Steers, 240-420kg: 10% increase

16,470 15,392 14,385 13,444 12,565 11,743 10,975

Steers, 240-420kg: 20% increase

20,485 19,145 17,893 16,722 15,628 14,606 13,650

Steers, 240-420kg: 30% increase

24,501 22,898 21,400 20,000 18,692 17,469 16,326

Steers, 240-460kg: 10% increase

16,096 15,043 14,059 13,139 12,280 11,476 10,726

Steers, 240-460kg: 20% increase

19,737 18,446 17,239 16,112 15,058 14,073 13,152

Steers, 240-460kg: 30% increase

23,378 21,849 20,419 19,083 17,835 16,668 15,578

67    

Appendix 9

2029 2030 2031 2032 2033 2034 2035 Year 14 15 16 17 18 19 20 Income Rent per hectare 200 200 200 200 200 200 200 Total Income 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Sensitivity Rent & Incomes

Steers, 240-420kg: 10% increase

264 264 264 264 264 264 264

Total Income 26,447 26,447 26,447 26,447 26,447 26,447 26,447 Steers, 240-420kg:

20% increase 329 329 329 329 329 329 329

Total Income 32,895 32,895 32,895 32,895 32,895 32,895 32,895 Steers, 240-420kg:

30% increase 393 393 393 393 393 393 393

Total Income 39,343 39,343 39,343 39,343 39,343 39,343 39,343 Steers, 240-460kg:

10% increase 258 258 258 258 258 258 258

Total Income 25,847 25,847 25,847 25,847 25,847 25,847 25,847 Steers, 240-460kg:

20% increase 317 317 317 317 317 317 317

Total Income 31,694 31,694 31,694 31,694 31,694 31,694 31,694 Steers, 240-460kg:

30% increase 375 375 375 375 375 375 375

Total Income 37,540 37,540 37,540 37,540 37,540 37,540 37,540 Expenditure No variable costs - - - - - - - Total Expenditure - - - - - - - Net Benefit/Cost (Base) 20,000 20,000 20,000 20,000 20,000 20,000 20,000 Steers, 240-420kg:

10% increase 26,447 26,447 26,447 26,447 26,447 26,447 26,447

Steers, 240-420kg: 20% increase

32,895 32,895 32,895 32,895 32,895 32,895 32,895

Steers, 240-420kg: 30% increase

39,343 39,343 39,343 39,343 39,343 39,343 39,343

Steers, 240-460kg: 10% increase

25,847 25,847 25,847 25,847 25,847 25,847 25,847

Steers, 240-460kg: 20% increase

31,694 31,694 31,694 31,694 31,694 31,694 31,694

Steers, 240-460kg: 30% increase

37,540 37,540 37,540 37,540 37,540 37,540 37,540

NPV Sums ( i = 7%) (Base) 7,756 7,249 6,775 6,331 5,917 5,530 5,168

Steers, 240-420kg: 10% increase

10,257 9,586 8,959 8,372 7,825 7,313 6,834

Steers, 240-420kg: 20% increase

12,757 11,923 11,143 10,414 9,732 9,096 8,501

Steers, 240-420kg: 30% increase

15,258 14,260 13,327 12,455 11,640 10,879 10,167

Steers, 240-460kg: 10% increase

10,024 9,368 8,755 8,182 7,647 7,147 6,679

Steers, 240-460kg: 20% increase

12,291 11,487 10,736 10,034 9,377 8,764 8,190

Steers, 240-460kg: 30% increase

14,559 13,606 12,716 11,884 11,107 10,380 9,701

68    

Appendix 9

NPV Sums (Base) NPV Sum 231,880.28 Steers, 240-420kg: (10%) NPV Sum 306,626.89 Steers, 240-420kg: (20%) NPV Sum 381,385.10 Steers, 240-420kg: (30%) NPV Sum 456,143.30 Steers, 240-460kg: (10%) NPV Sum 299,670.49 Steers, 240-460kg: (20%) NPV Sum 367,460.69 Steers, 240-460kg: (30%) NPV Sum 435,239.29

69    

Appendix 10: Gross margin calculation (steers 240-420kg)

                                    Growing out steers for feedlot market 240kg-420kg in 12 months             Year 2012 2013 2014 2015                 Income Sales revenue: 90% of steers 71,250.65 73,181.47 75,164.62 77,201.51         Sales revenue: 10 % of steers 7,923.50 8,138.22 8,358.75 8,585.27         Total Income 79,174.15 81,319.69 83,523.37 85,786.77                 Expenditure Steer Purchase 45,771.96 47,012.33 48,286.32 49,594.83         Cartage to property 1,030.90 1,058.84 1,087.53 1,117.00         Livestock & Vet costs 954.61 980.48 1,007.05 1,034.34         Other costs - - - -         Fodder crops: 12ha/100 steers 1,855.62 1,905.91 1,957.55 2,010.60         Hay & Grain (without drought) - - - -         Pasture maintenance: 100ha improved 4,999.87 5,135.36 5,274.52 5,417.45         Livestock selling cost 4,892.65 5,025.24 5,161.42 5,301.29    

   Total Variable Expenditure

59,505.61 61,118.15 62,774.39 64,475.52    

            Gross Margin 19,668.54 20,201.54 20,748.98 21,311.26                                            

70    

Appendix 11: Gross margin calculation (steers 240-460kg)

 

 

 

 

 

 

 

 

 

 

 

   

 

    Growing out steers for feedlot market 240kg-460kg in 12 months         Year 2012 2013 2014 2015         Income Sales revenue: 90% of steers 69,338.80 71,217.81 73,147.74 75,129.97     Sales revenue: 10 % of steers 7,541.46 7,745.82 7,955.73 8,171.32     Total Income 76,880.25 78,963.63 81,103.47 83,301.29         Expenditure Steer Purchase 41,109.96 42,224.00 43,368.23 44,543.46     Cartage to property 925.90 950.99 976.76 1,003.23     Livestock & Vet costs 857.38 880.62 904.48 928.99     Other costs - - - -     Fodder crops: 12ha/100 steers 1,666.62 1,711.78 1,758.17 1,805.82     Hay & Grain (without drought) - - - -     Pasture maintenance: 100ha improved 4,999.86 5,135.35 5,274.51 5,417.45     Livestock selling cost 4,401.73 4,521.01 4,643.53 4,769.36

   Total Variable Expenditure

53,961.45 55,423.75 56,925.68 58,468.31

        Gross Margin 22,918.80 23,539.88 24,177.79 24,832.98                                    

71    

Appendix 12: 330-400kg trade steer prices 2010-2015

National Livestock Reporting Service (NLRS) data provided by MLA, March 2015

Steer sale price C/kg

2010 2011 2012 2013 2014 2015 January 168 208 207 173 171 229 February 174 206 200 184 172 232 March 184 213 207 188 187 226 April 183 212 200 179 204 - May 181 198 193 171 198 - June 180 199 194 183 197 - July 182 207 207 190 201 - August 190 207 209 192 197 - September 196 208 198 188 201 - October 192 209 194 178 195 - November 194 208 186 178 187 - December 202 209 183 176 194 - Price Variation 34 15 26 21 33 5 Average Price 186 207 198 182 192 229

Growing out steers for feedlot market 240kg-420kg in 12 months (Appendix 10) + 20% increase in livestock prices

      Year 2015 2015+20% 2015-20%

Income Sales revenue: 90% of steers 77,201.51 92,641.81 61,761.21

Sales revenue: 10 % of steers 8,585.27 10,302.32 6,868.22

Total Income 85,786.77 102,944.14 68,629.43

   

Expenditure Steer Purchase 49,594.83 59,513.79 39,675.86

Cartage to property 1,117.00 1,117.00 1,117.00 Livestock & Vet costs 1,034.34 1,034.34 1,034.34 Other costs - - -

Fodder crops: 12ha/100 steers 2,010.60 2,010.60 2,010.60 Hay & Grain (without drought) - - -

Pasture maintenance: 100ha improved 5,417.45 5,417.45 5,417.45 Livestock selling cost 5,301.29 5,301.29 5,301.29 Total Variable Expenditure 64,475.52 74,394.47 54,556.54

   

Gross Margin 21,311.26 28,549.66 14,072.89