The Impact of Neighbourhood Density on the Energy Demand of Passive Houses and on Potential Energy

Sources from the Waste Flows and Solar Energy

by

Robert Stupka

A thesis submitted in conformity with the requirements for the Degree Master of Civil Engineering

Department of Civil Engineering University of Toronto

© Copyright by Robert Stupka 2010

ii

The Impact of Neighbourhood Density on the Energy Demand of

Passive Houses and on Potential Energy Sources from the Waste

Flows and Solar Energy

Robert Stupka

Degree Master of Civil Engineering

Department of Civil Engineering University of Toronto

2010

Abstract

This study demonstrates how the density of a neighbourhood affects its energy demand,

metabolism (energy and material flows) and its ability to produce its own energy. Single-family

detached houses and row townhouses were each modeled using passive solar housing guidelines

with the DesignBuilder building energy simulation software. Energy demand is then modeled

within neighbourhoods at two densities based on south facing windows fully un-shaded at 9:00

am, and 12:00 pm solar time on Dec. 21. The neighbourhood metabolisms were then calculated

based on location and density. The potential energy supply was evaluated from the spatial

characteristics of the neighbourhood (for solar) and the metabolism (municipal solid waste and

wastewater flows.) The potential energy demand and supply are then compared for the varying

building types and densities to determine the sensitivity of the energy supply and demand

relationships.

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Acknowledgments Thank you to Professor Kennedy for actively supporting all of my endeavours and diversions

during my research. Thank you for fostering my ideas and allowing me to join your wonderful

team. Thank you to the fantastic Sustainable Infrastructure Research Group. It has been

privileged to work with over the past two years. I will not forget the thoughtful conversation and

insights at pot lucks, pubs, coffee and camping. Hearing about your important research with the

noble goals of creating a more sustainable urban environment helped lift and inspire me through

the challenges while making my masters experience that much more enjoyable. Professor

Pressnail, thank you for my introduction to building science, showing me the potential impact

engineers can have to create a better world and always having an open door for my questions.

Thanks also to Professor Fung who was always more than happy to hear about my research and

offer advice. Jeff Quibell, you have been a great inspiration and mentor. Camille Jensen, thank

you for your love and encouragement to follow my passions and to seek out work with a positive

impact. Most importantly, thank you mom for always going above and beyond to help me

succeed.

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Table of Contents 1 Introduction .................................................................................................................................1

2 Review of Sustainable Neighbourhood Design ..........................................................................7

2.1 Regional and Community Energy Studies ...........................................................................8

2.2 Infrastructure and Energy ..................................................................................................11

2.3 Case studies of Community Energy Systems ....................................................................14

2.4 Passive Solar Communities................................................................................................15

2.5 Transportation ....................................................................................................................18

3 Net-zero Energy Buildings ........................................................................................................22

3.1 Building Energy Use ..........................................................................................................22

3.2 Passive solar building design .............................................................................................27

3.3 Renewable Energy .............................................................................................................39

3.3.1 Solar PV .................................................................................................................39

3.3.2 Solar Thermal Systems ..........................................................................................42

3.3.3 Ground Source Heat Pumps ...................................................................................45

4 Methodology .............................................................................................................................48

4.1 Low-Energy building model ..............................................................................................48

4.2 Passive Community Model ................................................................................................53

5 Results .......................................................................................................................................59

5.1 Building Energy Demand ..................................................................................................59

5.2 Urban Metabolism .............................................................................................................63

5.3 Energy Supply Potential ....................................................................................................64

5.4 Solar PV .............................................................................................................................65

5.5 Waste..................................................................................................................................66

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6 Conclusions ...............................................................................................................................69

References ......................................................................................................................................75

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List of Tables Table 1-1: Building scale and community scale opportunities for energy production and

integration. ...................................................................................................................................... 3

Table 2-1: Integrated resource recovery approach ........................................................................ 12

Table 2-2: Socio-economic, locational, and land use Influences on Auto VKT and Transit PKT in

the GTA ........................................................................................................................................ 19

Table 3-1: Average energy consumption for detached and attached single family houses from

2003 – 2007 in Canada ................................................................................................................. 22

Table 3-2: Building construction and energy use by era .............................................................. 23

Table 3-3: Predicted energy consumption for EQuilibrium houses .............................................. 27

Table 3-4: Comparison of House Standards ................................................................................. 28

Table 3-5: Sensitivity of building energy use and glazing of energy modelling parameters ....... 36

Table 3-6: Least cost optimal configurations of net-zero energy buildings in cities of varying

climates ......................................................................................................................................... 38

Table 3-7: Comparison of electricity loads R2000 Standard operating condition versus advanced

energy efficient appliances. .......................................................................................................... 39

Table 5-1: Major energy efficient appliances selected. ................................................................ 51

Table 5-2: Building characteristics ............................................................................................... 53

Table 5-3: Community characteristics .......................................................................................... 58

Table 6-1: Annual household energy demand scenario 1 ............................................................. 60

Table 6-2: Annual household energy demand scenario 2 ............................................................. 61

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Table 6-3: Energy Demand ........................................................................................................... 63

Table 6-4: Mass content of waste streams per year ...................................................................... 64

Table 6-5: Neighbourhood PV Production ................................................................................... 66

Table 6-6: Energy content of residual solid waste stream ............................................................ 67

Table 6-7: Potential energy production from waste sources ......................................................... 68

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List of Figures Figure 2-1: Relative contributions of lifecycle energy and GHG emissions between suburban low

density and urban high density development in Toronto. ............................................................... 8

Figure 2-2: Activity Intensity versus Passenger Car Use in 58 Higher-Income Cities ................ 20

Figure 2-3: Minimum densities for levels of transit service ......................................................... 21

Figure 3-1: Total annual energy consumption for conventional, R2000 and Advanced houses in

Canada ........................................................................................................................................... 24

Figure 3-2: Comparison of cumulative primary energy consumption for 80 year lifecycle. ....... 26

Figure 3-3: Flowchart of variables that influence building energy demand ................................. 30

Figure 3-4: Effect of temperature on PV efficiency ..................................................................... 40

Figure 3-5: Mean collector efficiency ratings ............................................................................... 44

Figure 4-1: Detached house model: South-east view (left), North-west view (right) .................. 50

Figure 4-2: Townhouse model: South-east view (left), North-west view (right) ......................... 50

Figure 4-3: Building spacing as a function of unobstructed solar access from different times of

the day on Dec. 21 for the detached house ................................................................................... 56

Figure 4-4: Building spacing as a function of unobstructed solar access from different times of

the day on Dec. 21 for the townhouse ........................................................................................... 56

Figure 4-5: Rendering of the neighbourhood scenarios evaluated................................................ 57

Figure 5-1: Scenario 1 internal gains ............................................................................................ 61

Figure 5-2: Scenario 2 internal gains ............................................................................................ 62

Figure 5-3: Heating and cooling requirements based on density .................................................. 63

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Figure 6-1: Potential electricity supply and demand from waste sources .................................... 72

Figure 6-2: Potential heating supply and demand from waste sources ......................................... 72

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1 Introduction It is widely recognized that cities have a central role in providing climate change solutions

(OECD, 2009). As of 2006, 80 per cent of Canadians lived in urban areas that account for 60 per

cent of energy consumption (Council of Energy Ministers, 2009). The energy use and GHG

emissions from urban areas is largely dependent on local climate, urban form, transportation

system, building policies, the energy supply and waste disposal (Kamal-Chaoui, et al. 2009,

Kennedy, et al. 2009). Cities’ responsibilities over such factors mean that their policies and

decisions can directly reduce their energy use and GHG emissions (Kamal-Chaoui, et al., 2009).

While agglomeration from increased urbanization facilitates the economic growth of a city, it

also provides significant opportunities for more efficient use of energy when all of the above

factors are considered. The urban metabolism has been commonly used to provide a picture of

the demands of a city, to compare the efficiency of its consumption of resources relative to other

cities and to evaluate its overall sustainability where the inflows of materials and energy do not

exceed the capacity of its hinterlands (Kennedy, et al., 2007). In identifying the producers and

consumers of these flows and their processes, the metabolism can be improved to create a more

sustainable city (Codoban, et al., 2008). Understanding the use of energy and potential for

production of energy in urban areas to take advantage of infrastructure integration is vital so that

new and existing neighbourhoods facilitate in meeting municipal and national climate change

mitigation goals instead of hindering them. Complimentary policies such as higher densities and

greater mixed land uses can reduce trip distances and frequency, and make frequent mass transit

feasible while providing opportunities for cascading of energy and district energy systems

(Kamal-Chaoui, et al., 2009).

One body searching for such integration is Quality Urban Energy Systems of Tomorrow

(QUEST), a collaboration of industry, environmental organizations, governments and academics

with the ultimate vision that all Canadian communities incorporate community energy systems.

Through deliberate infrastructure and land use planning based on seven strategies: increase

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density, increase complementary mixed uses, improve efficiency, optimize “exergy”1

The adoption of passively designed low-energy buildings could potentially reduce energy

demand to the point where it could be met from local energy sources. One such initiative that

attempted this on the building scale was the EQuilibrium housing project conceived by the

Canadian Mortgage and Housing Corporation (CMHC) in 2006. The project facilitated the

construction of 12 net-zero energy houses that are projected to require 80% to 88% less energy

than the average Canadian detached housing stock between 2003 and 2007 (NRCan 2009a,

Charron 2007). The houses are designed holistically to promote occupant comfort and health,

affordability, resource conservation and reduced environmental impact. The houses optimize

energy use through passive design and energy efficient appliances to minimize energy demands

so that the remaining energy required can be supplied from on site renewable energy sources

(CMHC, 2009). Because the renewable energy produced onsite is typically from intermittent

sources, importing energy from off-site sources the same amount of energy it produces on site is

often required (Wong, 2007).

, manage

heat, reduce waste and use renewable resources, Canada could reduce emissions by 65 Mt or 20

percent of the national 330Mt reduction target by 2020 (Bataille et al. 2009). On the community

level, integrated community energy systems could result in over 43% reductions (Jaccardet al.

1997, Bataille et al. 2009).

The American Institute of Architects (AIA) 2030 and new European building energy standards

are two larger scale initiatives to make carbon neutral and net-zero energy buildings more

pervasive. AIA has set the goal that all new buildings constructed by 2030 will be operationally

carbon neutral (AIA, 2009). These targets could be accomplished through innovative sustainable

design strategies, generating on-site renewable power and/or purchasing (20% maximum)

renewable energy and/or certified renewable energy credits (AIA, 2009). In Europe by 2019 all

new buildings are required to be constructed to net-zero energy and major renovations are to

meet minimum energy performance requirements (European Parliament, 2009).

1 Exergy is the maximum energy available for use before it becomes as equilibrium with its surroundings. QUEST uses this definition to optimise energy use by avoiding the using high quality energy for low quality energy applications (Bataille et al. 2009).

3

Expanding the net-zero energy concepts beyond individual buildings to the how communities are

designed can make best use of resources and infrastructure while providing more resilient and

cleaner energy sources. It would potentially provide greater design flexibility, financial and

energy economy of scale. Opportunities for seasonal storage, the sharing of heat sources

allowing for maximum utility, and smart micro-grids supporting electric power sharing between

houses, reducing utility peak demand would also be possible (Candanedo et al. 2009). Rooftops

could be optimized to be solar energy collectors and supply surplus energy to those with sub-

optimal orientation. Building heights and spacing could be optimized to maximize passive solar

heating and cooling. Buildings that are net heat producers could be situated in shaded areas and

provide surplus to nearby heat consumers. Material flows such as wastewater, solid waste and

organic waste generated by the community could also be harnessed for energy, creating an

integrated and diverse community energy system. Net-zero energy communities is the focus of

an upcoming follow-up EQuilibrium Communities project (CMHC 2010).

The combination of energy efficiency measures on the building level, identifying potential

energy sources and the influence of density to develop net-zero energy communities is the focus

of this thesis. The community scale provides greater design flexibility, and financial and energy

economy of scale. This could allow for opportunities for seasonal energy storage, sharing of heat

sources among buildings allowing for maximum utility, and smart micro-grids for electric power

sharing between houses, reducing peak demand of the power supplied by the utility (Candanedo,

et al., 2008). Additionally waste flows such as wastewater, solid waste and organic waste

generated by the community could also be harnessed for energy creating an integrated and

diverse community energy supply. A comparison between building scale opportunities and

community scale opportunities of energy producing technologies shown in Table 1-1

demonstrates some advantages of community scale adoption.

Table 1-1: Building scale and community scale opportunities for energy production and

integration. Energy System

Building Scale Community Scale

Ground Source Heat Pump

• Designed for at least 70% peak design heat load (CSA 448-2)

• Limited area on site • Unbalanced heating and cooling loads

resulting in inefficient use of system or

• Design as a commercial system with multiple buildings connected each with separate heat pump.

• Area required reduced, can take advantage of common areas such as parks, parking

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long term degradation of performance. lots, roads. • Provides economy of scale for the

installation. • Variability of loads allows for balancing of

system resulting in greater efficiency, lower capital and operating costs (smaller equipment due to smaller loops).

Solar Thermal • Provides either solar air or solar water

heating and can be integrated with a BIPV/T system.

• Overheating the system is an issue in the summer time as often design to supply fixed hot water loads year round (Hastings, et al., 2007).

• For heating, intermittent must use thermal mass to store heat during occupancy.

• Excess heat in the summer could recharge the ground if loads are unbalanced to maintain GSHP performance.

• Excess heat can be utilized in swimming pools or other common facilities.

• Excess heat can suppliant heating needs of other buildings.

• Harnessing of solar thermal energy can be maximized for thermal energy storage for winter heating.

Solar PV • Intermittent, must be tied to grid or battery. • Performance degrades with heat possible to

mitigate with BIPV/T. • Building roof must be able to support and

ideally azimuth within 22.5 degrees of south (Erley, et al., 1979).

• Can maximize suitable roof area and sell excess electricity to the grid.

• Smart grid allows use of energy from other sources eliminating problems with intermittence.

• Reduce transmission losses by providing power to local buildings with schedules that better coincide with solar availability.

Wastewater • Drain heat recovery. • Grey-water system for irrigation and toilet

flushing.

• Heat generated from anaerobic digestion distributed to the community.

• Bio-methane captured for vehicles.

Organic waste • Local soil compost. • Heat generated from anaerobic digestion distributed to the community.

• Bio-methane captured for vehicles. Solid Waste • Transport off site. • Methane captured at landfill.

• Incineration Energy Distribution System

• Heat recovery ventilator. • Excess heat is exhausted. • Water drain heat recovery.

• District energy system. • Excess heat is distributed to other

buildings. • Can incorporate a diversity of heating or

cooling sources. • Reduce space required for mechanical

equipment. • Reduce equipment and maintenance cost.

This study examines neighbourhood scale opportunities for reducing energy use through passive

design and local energy production and the influence of potential supply and demand

relationships on density. In working toward the AIA 2030 challenge and municipal climate

change goals in the wake of increasing urbanization what is the path to developing net-zero

communities?

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Given the intermittent and spatial variance of the availability of renewable energy, and the need

for the supply to meet the community’s energy demands, Born et al. (2001) suggests two

approaches to integrate renewable energy systems within the built environment:

1) The energy source capture area is greater than that occupied by the community to be supplied; or,

2) Reduce the community’s energy demands to a level that will match the locally available renewable energy resources (Born, et al., 2001).

This study adopts the latter approach. The objective is to determine the importance of density on

building energy demand and supply of a community.

Density impacts energy demand by increasing shading of neighbouring buildings which can

reduce cooling loads and increase heating loads. Many low energy building design guidelines

and programs do not consider the impact of neighbouring buildings on energy use and the

applicability of the guidelines. Modeling the performance of buildings in a neighbourhood

context at various densities is important to determine the applicability of the design guidelines

and the sensitivity of energy demand with density. Density also reduces transportation energy

and could use space more efficiently by increasing the number of roof tops that could harness

solar energy and increase the waste flows that travel through the community which are potential

energy sources.

The objective of this thesis is to study the impact of density on energy demand passive houses

and to explore the impact of density on potential energy sources from the waste flows and solar

to achieve a net-zero energy community. Two building models: detached and row houses, based

on passive design principles are developed. Each building type is then modeled into two

neighbourhood scenarios of different building spacing resulting in variations of solar access and

building energy demand. The spacing establishes the density and total energy demand for the

neighbourhood scenarios. The waste flows through the neighbourhood and the potential for solar

PV is then determined to determine the relationship between the potential energy supply and

demand with density. The relative order of magnitude of potential energy from each energy

source compared to the demand will determine which sources yield the greatest energy potential

and which scenario is closest to becoming a net-zero energy community.

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This thesis begins with an introductory chapter followed by a literature review organised in two

chapters. Chapter 2 is a review of sustainable neighbourhood design and Chapter 3 is a review of

the design of net-zero energy buildings with both passive and active techniques / technologies..

Chapter 5 describes the context, scope and methodology used which is based on a combination

of the neighbourhood and building design best practices described in the literature review. It

describes the development of two low energy houses, a detached house and a townhouse and

modeling their energy demand in a community context in four scenarios. It also evaluates the

sensitivity of energy demand on restricted solar access and compares the results with the results

of buildings modelled in isolation. Chapter 6 presents the results of the building energy models

and the evaluates the potential energy supply for the neighbourhoods at the varying densities

based on the roof area available for solar photovoltaics (PV) and solid and liquid waste flows

through the community. Chapter 7 presents the conclusions of the thesis. Insights into the

development of the passive building models are discussed as well as how energy performance

and design considerations change in a neighbourhood context from an isolated building. The

potential energy supply and demand for heating and electricity are compared. Although it was

found that the material flows through the community could not meet all of the community’s

energy demand, (12% to 20% of heating demand and 15% for electricity demand) the quantities

are not trivial. The increased density townhouse scenario was able to produce 66% more of its

heating demand than the low density detached house scenario. The electricity supply and demand

relationship from waste flows was found to be relatively insensitive to density and was therefore

constant in all of the scenarios. The potential PV production however, is able to produce between

2.9 and 4.3 times the total electricity demand. Increased density in the townhouse scenario

resulted in reduced PV production on a per unit basis. Therefore tradeoffs exist between

increased thermal efficiency and density of the townhouse scenario and the solar availability for

PV production.

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2 Review of Sustainable Neighbourhood Design This chapter reviews regional and community energy studies, their methodologies and the

technologies considered. This is followed by discussing opportunities for community energy

systems from the infrastructure that services the community and presents case studies of

community energy systems. Community passive design principles such urban form such as street

layout, building orientation and landscape features to facilitate low energy communities are then

discussed.

The literature of energy use and production of communities consists of studies that evaluate an

entire urban region or case studies of particular master planned districts. Energy use and

greenhouse gas emission in urban regions especially in Toronto have been well studied (Torrie

Smith and Associates 1997, Norman, et al. 2006, VandeWeghe, and Kennedy 2007 and

Kennedy, et al. 2009). These studies generally show that energy use varies significantly in urban

regions depending on climate, spatial factors, land-use, access to transportation systems, building

codes and the age of the building stock. There is a strong correlation between GHG emissions

and energy use for particular regions with the carbon intensity of energy sources being the most

important factor of a region’s carbon footprint.

In Toronto, building operations account for 50% of total residential emissions followed by 36%

transportation related and 14% from waste; however, variations among neighbourhoods were

found to differ by over a factor of 4 with auto use in suburban areas the primary factor. Kennedy

et al. (2007) and Norman et al. (2006) found that lifecycle energy use for suburban low-density

development was higher by a factor of 2 to 2.5 than high density urban core development on a

per capita basis 1.0 to 1.5 on a per unit of living space basis (assuming similar era of

construction), Figure 2-1. The study by Norman, et al. (2006) particularly demonstrates the

importance of the functional unit when comparing residential energy use as the number of

occupants per unit and unit size affect the relative efficiency in energy use. For example high

density residential and low density residential buildings are not equivalent in occupancy or size

and therefore are difficult to compare as a choice of one over the other. It also demonstrates that

energy use requires study beyond the building level to the neighbourhood level to account for the

variation in transportation energy for building types and location. Neighbourhoods have many

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interactions with the larger urban system that affect building and transportation energy use,

infrastructure and environmental impact, therefore both micro and macro scale conditions must

be understood (Engel-Yan, et al., 2005).

Figure 2-1: Relative contributions of lifecycle energy and GHG emissions between

suburban low density and urban high density development in Toronto.

Source: Figure 6 in Norman, et al. (2006)

2.1 Regional and Community Energy Studies The definition of green energy used in this study will be energy that does not deplete the Earth’s

resources and results in no or low emissions of greenhouse gases, sulphur oxides and local air

pollutants (BC Hydro & Alternative Energy Division, 2002).

Most methodologies for assessing regional and community level renewable energy potential

reviewed involved a high level analysis. Approaches include reviewing of agricultural land data

to determine locally available biomass, mapping analysis to determine potential hydro, solar and

wind resources, calculating areas to determine suitable for solar and wind, and statistical

sampling of building types for actual neighbourhoods. Below is a summary of some of the

approaches reviewed:

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o Grant and Kellett (2002) quantified the potential availability of local energy sources for

the municipality of Conisbrough-Denaby, UK. The toal solar, biomass and wind and

hydro potential was quantified called the resource base. This potential was the classified

as either the resource: the part of the resource base that could be utilised using existing or

modified currently available technology under present or future economic conditions, or

the reserve: the part of the resource that could be exploited under prevailing economic

circumstances (Grant, et al., 2002).

o Ghosh and Vale (2006) determined the solar energy potential for a New Zealand

neighbourhood by using GIS to calculate the roof area suitable for solar thermal and solar

PV (Ghosh, et al., 2006).

o Vadas et al (2007) assessed carbon mitigation measures and associated costs on a

regional scale for Tompkins County, New York using geographical and statistical data.

The study consisted of five primary categories: terrestrial carbon sequestration, local

power generation, changes in utility operations at Cornell University, changes in the

transportation sector, and energy end-use efficiency measures. Vadas found that 69% of

carbon could potentially be mitigated with 29% at no net cost to the consumer (Vadas, et

al., 2007).

o Wong (2007) conducted a feasibility study of a community energy system for a

community in London, Ontario. The report studies a predetermined community layout

consisting of a mix of 52 townhouses, two eight-storey multi-unit residential buildings,

and one commercial office building. The technical, economic, social, regulatory and

business feasibility was assessed for the combining of advanced sewage collection,

anaerobic digestion of organic waste, combine heat and power generation, aquifer

thermal energy storage (ATES), active solar heating and air source domestic hot water

heat pumps. Building energy loads were estimated using EED building energy

simulation software while TRNSYS was used to simulate the district heating and cooling

system. HST3D was used to model ground water flow and heat in the ATES system. The

strategies were able to achieve 86% reduction of energy imported into the community

(Wong, 2007).

o Hamilton (2008) created an ‘ideal’ renewable energy assessment method for local

government based on a review of the above studies and applied it to a renewable energy

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resource assessment for the City of Playford, Australia. The maximum renewable

resource (solar, wind and biomass) available was determined using spatial and

demographic data from the case study area. Solar resource was calculated using GIS to

determine available north facing roof area for residential, commercial and industrial

buildings. A sample of each building type and era (for residential building) was

inspected to determine roof angles and total solar resource for the population. Wind

resource was determined by identifying areas suitable for potential wind turbines using

fishnet tool in ARCGIS. Suitable turbine locations were based on predefined setback

distances, land uses, and spacing criteria to determine the total number of potential

turbines. Average wind speed from two monitoring sites and different turbines was used

to determine the total potential size of the wind reserve. Animal and human waste was

calculated from census data and wastewater data from the government to determine the

potential for methane recovery. Animal waste based on the number of animals and total

dissolved solids produced by each animal per year. Domestic waste was based on

municipal data assuming the capture of landfill gas and an estimate based on limited

information was made for wood and green waste available based on the number of

households and forestry operations in the area to calculate the total potential biomass

resource (Hamilton, 2008).

o O’Brien et al. (2009) studied the relationship between net energy use (inclusive of

transportation energy) and urban density of solar buildings. He analysed three different

scenarios: low-density neighbourhoods located in the outer suburbs, medium density

located in inner suburbs, and high-density neighbourhoods located in the inner city of

Toronto. A conceptual community layout was developed so that orientations maximised

south-facing facade solar exposure. Household energy use was obtained from publically

available statistical data for each housing type and was broken down to energy use per

person (KW/capita) and energy use per area of floor space (KW/m2). Specific impact of

shading on building energy demand was not analysed. The total area available for solar

collectors on facades and roofs was calculated to determine the total energy potential for

each building type. Transportation energy use determined from a land use transportation

model which was developed from regression analysis of transportation behaviour survey

data for the City of Toronto. The study found that while low density dwellings were able

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to meet more their energy needs with solar on a per capita basis, the gains were offset

higher transportation energy use (O'Brien, et al., 2009).

The level of analysis in the studies varies considerable from very high level regional studies to

specific case studies for a particular site involving detailed computer models. Many do not model

the combined and dynamic intermittent nature of the availability of the renewable energy sources

and energy demand. Regional studies particularly rely on resources found outside of the

community scale. None of them account for the the supply and demand relationship and its

sensitivity with density, although O’Brien (2009) provides an order of magnitude of energy

demand based a high level analysis of reported energy demand for typical buildings and

transportation energy use. This study combines detailed building energy demand modelling with

a higher level analysis of how potential energy sources are impacted in a community context

with density.

2.2 Infrastructure and Energy Neighbourhood sustainability requires infrastructure systems at the urban scale to support micro-

scale goals (Engel-Yan, et al., 2005). In fact, decisions in the management of energy, climate

change and air pollution are also similar to those associated with water and waste (Bataille, et al.,

2009). Infrastructure is the conduits that interact the building with the community and the greater

region. They provide services to “nourish” individual buildings by supplying energy, water,

waste disposal, communication and transportation. Developments and municipalities rarely take

into account many of these effects resulting in needless inefficiencies, end of pipe solutions and

missed opportunities for symbiosis to create a community that minimises its ecological footprint.

By integrating land-use and transportation planning, management of solid waste, liquid waste,

potable water, energy systems and greenhouse gas reduction strategies, our cities’ infrastructure

could become more efficient and will be able to maximise the recovery of “value” from waste

resource streams providing a new net revenue source for the municipality (Slater, 2009). The

conventional approach to waste management is to collect waste and discharge or stored into

designated areas for storm water or solid and wet organic waste or collected and treated before

discharge with wastewater. Table 2-1 however, shows that there are numerous opportunities to

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reuse a waste product or transform the wastes into nutrients for agriculture and potential energy

sources.

Table 2-1: Integrated resource recovery approach Resource When is it Waste? Conventional

Approach IRR Approach

Storm Water When reaching drainage systems

Collect and discharge to receiving environment

• Collect, treat, and reuse on-site;

• Divert to ecological uses; reduce amount of impermeable surfaces through water sensitive urban design; and

• Follow natural drainage and hydrology.

Waste Water When reaching

collection systems Collect, treat, and discharge to receiving environment

• Collect, treat, and reuse water for regulator-approved non-potable purposes.

Biosolids When produced by

wastewater treatment plants

Collect and landfill, or apply to Industrial Landscaping

• Collect and divert to composting or anaerobic digestion to produce biomethane; and

• Recover nutrients through regulator-approved use of residuals.

Wet Organic Waste (e.g. food waste, agricultural waste)

When produced by farming as well as processing, retailing, preparation and consumption of food

Collect and landfill • Collect and divert to composting or anaerobic digestion to produce biomethane; and

• Recover nutrients through regulatory-approved use of residuals.

Dry Organic Waste (e.g. Yard waste, wood residuals, non-recyclable paper)

After initial use Collect and landfill • Collect and divert to composting or to energy production; and

• Recover nutrients through regulator-approved use of residuals.

Source: Section 3 (Slater, 2009)

Improved complementary mixed uses can better facilitate solar distribution since buildings that

are net heat producers due to high internal gains would benefit from shading while buildings that

require heat can have priority solar access and even benefit from waste heat from the other

buildings. Opposite occupancy schedules can utilize the energy infrastructure more efficiently by

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distributing demand more evenly through a district energy system. The district energy system

could take advantage of load diversity among building types reducing overall infrastructure size,

create economies of scale for local energy producing infrastructure, and enable sewage heat

recovery, combined heat and power, geo-exchange and other renewable energy technology

(UBCM, 2009). District energy systems could allow for renewable and non renewable energy

sources in the same system which could permit fuel switching depending resource availability

and provide flexibility if prices for certain energy sources fluctuate (Wilson, 2007). Engineering

and equipment costs could be greatly reduced in a district system because a boiler is not required

in every building. This could result in valuable space savings and reduced maintenance costs

(Wilson, 2007). The additional space could be the most significant savings for some

developments (Wilson, 2007).

A report by the Canadian District Energy Association, The Toronto Atmospheric Fund and the

Canadian Urban Institute describes a four step process they developed to identify communities

that could be suitable to develop district energy (Gilmour, et al., 2007):

1. Identifying high growth areas that were expanding or areas that will be focused for

revitalisation;

2. Assessing urban form for sites with high density, mixed uses and load diversity;

3. Developing a land use site profile of building area and type, existing and projected

growth and determining the local utility prices, and;

4. Calculating the energy intensity factor for the development which characterises the

density of energy use. The factor combines the estimated annual space heating, cool and

hot water energy demand per square metre of land including losses (GJ/yr/m2). This

provides a relative sense of infrastructure costs as higher average intensity will require

less infrastructure (Gilmour, et al., 2007).

The best sites for district energy are locations that have a high density energy demand and mixed

uses to provide stability to the demand (Gilmour, et al., 2007). High energy intensity areas

reduce the length of the infrastructure required reducing costs and energy losses (Gilmour, et al.,

14

2007). Generally, buildings are recommended to be within 200 to 300 metres apart with the

main energy source plant and no more than 1 to 2 km away from the largest buildings (Wilson,

2007). Mixed use provides load diversity that makes more efficient use of energy supply systems

over systems designed for a single building (Gilmour, et al., 2007).

2.3 Case studies of Community Energy Systems Several examples of Canadian communities that have developed or are exploring opportunities

for community energy systems are described in this section. They demonstrate the diversity of

opportunities and how the availability of resources, climate, and location has influence the

choice of a particular system.

Toronto – District cooling of downtown core up to 20% of the downtown building load. Water

pumped for the Island Filtration Plant from the cold, deep waters of Lake Ontario intercepts with

a series of heat exchangers that separate the potable water supply and the district cooling loop.

Water enters the district system at 2.4oC to 4oC and leaves the system at 12oC. Ultimate cooling

capacity can displace 36 MW of Toronto’s electrical demand (Sustainable Edge Inc., 2004).

Revelstoke – Established the Revelstoke Community Energy Corporation that provides a 1.6 km

long low temperature district energy system. The system delivers steam to local industry and hot

water for space and water heating for building via the burning of wood waste from nearby

Downie Mills. The system is a new revenue source for the city, displaces 45,000 GJ of fossil

fuel energy, has saved the saw mill from closure, improved air quality and reduces GHG

emissions be 3,700 tonnes annually (NRCan, 2009e).

Whistler Athletes Village – The Municipality of Whistler Partnered with Terasen Energy

Services to develop a district energy system for the Whistler Athlete’s Village. The system

attempts to make use of a variety of low grade heat sources ranging in temperature from 5oC to

45oC upgraded with heat pumps in every building (Wilson, 2007). The low-grade heat sources

allow the system to un-insulated distribution pipes. The primary sources of heat are from closed

and open loop geo-exchange, landfill gas, wastewater treatment plant effluent (McDonald, et al.,

2008).

15

Drake Landing – 52 single family homes constructed to the R2000 standard connected to a

district borehole thermal energy storage (BTES) system that supplies 90 percent of heating and

60 percent of hot water needs (NRCan, 2009d).

Southeast False Creek – A Neighbourhood Energy Utility (NEU) was established to provide both

water and space heating to all new buildings in the community. The system is designed to use a

variety of waste energy opportunities that would not be available at the individual building scale.

70 percent of the heating demand is supplied from sewage heat recovery from untreated sewage

(City of Vancouver Sustainability Group, 2008). The heat is extracted via a heat pump with a

COP of 3.5 to upgrade the low grade thermal energy to 65oC. The remaining demand is supplied

by solar thermal collectors and by backup high-efficiency natural gas boilers. Cooling is

provided using air source heat pumps that reject heat into the parkade eliminating the need for

roof top cooling towers (NRCan, 2009b). Overall GHG emissions are 50 percent less than

conventional energy sources (City of Vancouver Sustainability Group, 2008). The development

currently services 585,000 m2 of development, 85 percent of which is residential on an 80 ha

site. Future plans are to extend the system to 1.2 million m2 of floor space (NRCan, 2009b).

2.4 Passive Solar Communities

In 2001, 8% of home heating needs in Canada are provided by passive solar heating; however,

minor changes in community planning, building design and higher standards from could increase

that proportion to 22% across the average building stock by 2020 (David Suzuki Foundation,

2004). In Ontario, housing stock with optimal solar exposure for passive solar could increase

from 12% in 2001 to 23% by 2025, if good solar orientation design in implimented starting in

2008 (David Suzuki Foundation, 2004). This could also increase the housing stock suitable for a

3 kW solar array from 47% in 2001 to 51% in 2025 and the housing stock suitable for single

family dwellings from 63% in 2001 to 77% in 2025 (David Suzuki Foundation, 2004).

DOE and the national laboratories are currently studying the potential for net zero energy use at

the community or campus level to use renewable energy sources beyond the building footprint

more effectively (Pless, et al., 2009). The EQuilibrium Communities initiative from NRCan is a

derivative of CMHC’s Equilibrium housing project whose aim was to push the advancement of

energy-efficient design with renewable energy (CMHC, 2007). The EQuilibrium Communities

16

initiative extends this to the community scale by engaging development teams to market energy-

efficient, sustainable and profitable communities that benefit consumers, the environment, and

the economy (CMHC, 2009). NRCan also has an ongoing Urban Archetypes Project which looks

at how urban form and location influences household energy and vehicle usage (NRCan, 2009c).

The site location has a significant impact on the heating and cooling demands of a building as

well as potential for on-site energy generation. Local weather conditions such as temperature,

solar irradiance, wind speed and direction and relative humidity all determine what design

strategies are most suitable for a particular site. External factors such as vegetation, neighbouring

buildings, terrain and atmospheric pollutant conditions can are local factors that can helpfully or

adversely affect site energy requirements. Buildings and lot lines often follow roadway

alignment; therefore orientation and street pattern are critical characteristics to maximize solar

access. Generally, east-west streets are preferred (M.M. Dillon Limited, 1979).

On-site and off-site shading sources including self shading features, terrain, neighbouring

buildings and vegetation should be evaluated in order to benefit overall building energy use.

South facing walls should be un-shaded in the winter to maximise solar gain and fully shaded in

the summer. The winter sun path that should remain unshaded for passive solar heating is

defined by the sky space bounded by the solar altitude between December 21st and

March/September 21.

Appropriately placed trees and vegetation can effectively shelter the building from wind and

shade in the summer however solar collectors should remain un-shaded year round. CMHC

(1998), recommends that trees be avoided directly south of the house. Trees are best if located to

the west and east side of the house positioned at least at a 30 degree angle from the north-south

axis (CMHC, 1998). Additionally, conforious trees are recommended located on the north and

west side to provide a windscreen (M.M. Dillon Limited, 1979). M.M. Dillon Limited (1979)

and CMHC (1998) include tables that compare the shading and wind shielding characteristics of

various trees. Erley, et al. (1979) provide siting guidelines for regions in the United States that

account for climate and terrain.

Solar thermal collector efficiency is particularly affected by cooler surrounding air in shaded

areas and cool local winds (Erley, et al., 1979). Features should be evaluated by the shadow

17

pattern formed in mid-winter projected at 45 degree angles from the north-east and north-west

corners of the object (Erley, et al., 1979). The sky space for domestic solar hot water collectors is

defined by the solar altitude between December 21st and June 21st; however, since more heat than

is required may be generated during the summer a reduction in efficiency may not be as critical

and the cool effect of shading may be preferred (Erley, et al., 1979). The reference height of the

sky space depends on whether the entire south wall access is to be unobstructed or only the roof

(Erley, et al., 1979). Studies have shown that active solar collector efficiency is not as sensitive

to orientation as passive solar features; 95% of solar potential can be provided within 30 degrees

of south (Hastings, et al., 2007).

While density provides significant benefits to increase the efficiency of infrastructure, there are

also tradeoffs in the availability of solar access. Because the amount of solar energy received

over an area is fixed, the site layout should maximise the availability of solar radiation for

buildings for passive solar heating and solar PV/T applications. Still, increased density will

result in less solar resource available per capita and require other means to meet its energy

demand despite that overall energy demand on a per unit basis decreases with density (O'Brien,

et al., 2009).

Solar aperture ratio is a good indicator of solar availability in the development. It is the ratio of

the area of a development exposed to the sun at solar noon during summer solstice to the area

exposed to the sun during the winter solstice. In the northern hemisphere, it is desirable to

minimise solar gains in the summer and maximise solar gains in the winter, therefore, a lower

solar aperture ratio would provide a more efficient design (Rickaby, 1987). If hourly simulation

is conducted on the neighbourhood over the heating and cooling seasons, the ratio could be

calculated in terms of square metre hours and divided by the total overall surface area (Knowles,

1974). In such case, the efficiency of the built form is described by accounting for the area of

heat loss to the area of solar exposure (Rickaby, 1987).

With passive and active solar energy becoming an increasing part of the total energy supply, the

protection of solar access (solar rights) and equitably of its distribution needs to be recognised in

planning community density, standards, and zoning (Rao, et al., 1987).

18

2.5 Transportation Transportation energy use is dependent on the outcome of interrelated locational, land-use,

socio-economic and transportation infrastructure factors. Residential transportation can account

for as much as 20 – 40% of a neighbourhood’s energy use and 30 – 60% of lifecycle GHG

emissions (Norman, et al., 2006). IBI (2001) found that in Toronto, transportation emissions

between high-density centrally located dwellings had 2.7 times fewer emissions then a low

density suburban dwelling. VandeWeghe, and Kennedy (2007) found that in Toronto GHG

emissions from private auto use in the central core accounted for on average 30% of GHG

emissions while in the surrounding regions 60% of emissions are attributed to private auto use ().

Therefore, where and how communities are developed is just as important as the buildings that

make them up from a total energy and GHG emissions perspective.

In 2000, IBI published a report and accompanying analysis tool for predicting vehicle kilomters

travelled (VKT) and greenhouse gas emissions of neighbourhoods (IBI Group, 2000). The study

used multi-variable regressions anaylses on socio-economic, locational and neighbouhood design

variables based on the data from the 1996 Transportation Tomorrow Survey data (IBI Group,

2000). The key variables determined from the study that affect VKT and passenger kilometers

travelled (PKT) in the Greater Toronto Area (GTA) are shown in Table 2-1. Of the variables

tested, auto ownership was found to have the strongest influence on VKT which in turn was

depenent on locational characteristics. Vehicle ownership in inner areas was on average 0.6 per

household where wereas ownership was 1.72 in the outer suburbs (IBI Group, 2000). The study

also found that Neo-traditional developments in the outer suburbs had 14% fewer annual GHG

emissions than conventional conventional suburban developments, though they both still had

between 37% to 58% more emissions than their inner area counterparts. While neighbourhood

form can provide moderate reductions in GHGs. This demonstrates that with transit-supportive

planning, transportation emissions reductions can be achieved in any neighbourhood however,

the impact good micro urban form can be limited, if macro infrastructure such as rapid transit is

not available or it becomes an “island” surrounded by auto-dependent development.

19

Table 2-2: Socio-economic, locational, and land use Influences on Auto VKT and Transit PKT in the GTA

Auto VKT Transit Travel PKT Distance to the CBD Vehicle Ownership Employment within 5 km People per household Land-use mix Personal Income Distance to regional or rapid transit stations, whether road layout type is rural, and the number of intersections per road-km are also statistically significant.

Local transit service is tied with the number of people in a household Auto ownership Distance to the CBD Neighbourhood housing densities

Source: IBI Group (2000)

Green (2006) studied the impact of good micro and macro urban form in the GTA. Good urban

form were defined as those with both good micro measures: land use mix of greater than 30%

residential area and greater than 18% commercial area and good macro measures: within 1 km of

a subway stop and/or light rapid transit (LRT) stop.

The study found that neighbourhoods in the GTA with good micro and macro urban form

(GMM) an average of 53% of trips were conducted by transit, walk and cycle and had lower

vehicle ownership rates. In absence of higher order transit, good micro neighbourhoods still

achieved average mode splits by alternative modes of 37%. (Green, 2006). In suburban areas

with good micro transit oriented urban form but no rapid transit, significant portions of internal

zone trips still occur using alternative modes however, external trips were automobile dominant

resulting in an overall alternative mode split of just 12% (Green, 2006).

Newman and Kenworthy’s studies published in 1989 on the relationship between GHG

emissions densities of 32 major cities around the world show that the two are highly related.

From a land use policy and vehicle emissions standpoint, the studies suggest a 30% reduction in

driving every time density doubles suggesting that sprawling suburbs would benefit the most

from modest increases in density (Newman et al. 1989, Holtzclaw, 2000). This trend was further

confirmed with an expanded study in 1995 of 58 high income global cities Newman, et al.

(2006), Figure 2-2 and in 2009 by Kennedy, et al., (2009).

20

Figure 2-2: Activity Intensity versus Passenger Car Use in 58 Higher-Income Cities, 1995.

Source: Figure 2 (Newman, et al., 2006).

Studies are mixed about the direct impacts of density on travel behaviour mainly because

increased density is interrelated with many other factors such as distance to the central business

district, the availability of high quality transit infrastructure and higher costs of parks and density

by itself in not very significant. However when it enables of cost-effective transit service and

land use mix, provides short walking distances to attractions and destinations, it shown to be the

one of the most effective factors that reduces auto dependency. Figure 2-3 illustrates minimum

residential densities required to support various levels of transit service. The figure shows two

important thresholds. The first is that a minimum headway of 30 minutes is required to support

TOD. The corresponding minimum density to support this level of service is 17 units per hectare.

Densities below 17 units per hectare are considered to be conventional sprawl (Central Okanagan

Smart Transit Plan Transit-Supportive Guidelines, 2008). The second threshold is the

recommended minimum frequency (headway) during off-peak hours required to attract riders to

transit who have access to other modes of transportation such as SOV. Transit service headways

longer than 15-minutes are shown to be a large disincentive for users with other transportation

options while making life without an automobile easy (Transit Oriented Development Traveler

Response to Transportation System Changes, 2007). Achieving this level of service is especially

21

important to entice existing suburbanites who already have automobile access to transit and so

that new populations will have lower vehicle ownership rates and corresponding lower VKT.

Figure 2-3: Minimum densities for levels of transit service

Conventional Spraw

l

Places to Grow (minimum average greenfield density)3

Freq

uenc

y of

Tra

nsit

serv

ice

(min

utes

)

Population Density (units per hectare)10 20 30 40 50 60 70 80

10

20

30

40

50

60

30 60 90 120 150 180 210 240

1 hour bus service (conventional sprawl)1,2

½ hour bus service (min. TOD density)1,2

10 minute bus service (BRT, GLT)1,2

Conventional Bus/Shuttle Bus

Conventional Bus

Rapid Transit (BRT, GLRT, LRT, ALRT, Subway and Commuter Rail)

Shuttle Bus

Transit Oriented

Developm

ent

Minimum headway to attract riders who have automobile access4

Minimum TOD frequency IBI1

5 minute rapid transit service1

local bus service, ITE2

Intermediate bus service, ITE2

Frequent bus service, ITE3

1 Central Okanagan Smart Transit Plan Transit-Supportive Guidelines2 Ontario Transit Supportive Land Use Planning Guidelines 1992 3 ITE recommended Minimum Transit Service versus Residential Densities4 Recommended headway in TCRP Report 95 Transit Oriented Development Chapter 17

Places to Grow (minimum density UGC)

Population Density (persons per hectare)

22

3 Net-zero Energy Buildings

3.1 Building Energy Use

Buildings consume 33% of energy produced, 50% of natural resources and 12% of water,

generate 25% of landfill waste, 10% of airborne particulates, and 35% of greenhouse gases in

Canada (CaGBC, 2007). As such, buildings have both significant environmental impacts yet

provide tremendous opportunities to reduce energy consumption and greenhouse gas emissions

on a large scale.

The average household (HH) energy consumption for detached and attached single family houses

in Canada is provided in Table 3-1. Heating is by far the greatest component of energy demand

(57-65%). Both average household energy intensity kWh/m2 and average energy use per

household have been steadily decreasing over the last 20 years primarily due to increasing

energy efficiency in building codes, however, potential efficiency gains are lost due to growth in

the number of appliances, the use of air conditioning systems and household size (NRCan,

2009a).

Table 3-1: Average energy consumption for detached and attached single family houses from 2003 – 2007 in Canada

Single Detached Single Attached

kWh/m2 kWh/HH kWh/m2 kWh/HH Space Heating 163 25300 126 16250 Water Heating 40 6150 46 5980 Appliances 29 4570 32 4150 Lighting 12 1840 10 1310 Space Cooling 5 761 6 806 Total 249 38600 222 28500

Source: NRCan (2009a).

There have been several initiatives in Canada to encourage to construction of more energy

efficient houses. The R2000 program established in 1981 by Natural Resources Canada and the

Canadian Home Builders Association consists of a construction standard and quality verification

and certification process to encourage energy efficient construction into the marketplace. R2000

houses cost-effectively typically consume 30% less energy than conventional comparable non-

R2000 houses (CHBA, 2007). The standard is periodically updated to account of new innovation

in construction to continue to represent advances new home construction (CHBA, 2007). Table

23

3-2 shows the evolution of energy consumption and building construction for a house in Toronto.

A house constructed in the 1930s consumes 2.7 times as one of similar size constructed to the

R2000 standard (Dong, et al., 2005).

Table 3-2: Building construction and energy use by era

Era Description Annual energy use per gross floor area (GJ/ m2)

Annual energy use per gross floor area after basement and air leakage retrofits (GJ/ m2)

Pre- World War II 1930s

Solid masonry construction without any additional wall or foundation insulation, block or masonry foundation basement. (R10 attic insulation; and 15 ACH @ 50 Pa air tightness)

1.91 1.49

Post-War 1960s

38 x 140 mm (2”x4”) Wood-frame construction, masonry veneer, exterior walls insulated to 1.76 RSI (R10), foundation un-insulated. (R14 attic insulation; and 8 ACH @ 50 Pa air tightness )

1.45 1.12

Post-Oil Crisis 1980s

38 x 140 mm (2”x6”) Wood-frame construction, masonry veneer, exterior walls insulated to 3.5 RSI (R20) with partial basement insulation (2.1 RSI (R12)) to 600 mm below grade. (R22 attic insulation; and 3 ACH @ 50 Pa air tightness )

0.92 0.83

R2000 house 0.71 Not applicable Source: Table 2.3 (Dong, et al., 2005)

In 1991, the Canadian Centre for Mineral and Energy Technology (CANMET) at Natural

Resources Canada (NR-Can) launched the Advanced House program with a purpose to

encourage research and demonstrate and evaluate energy efficiency and low environmental

impact construction in the residential building sector (Proskiw, 1996). A total 10 houses were

constructed in different climate zones. Overall, the advanced houses were able achieve 65%

energy reduction over conventionally constructed houses at the time or consumed on average

14,000 kWh/a (Figure 3-1).

24

Figure 3-1: Total annual energy consumption for conventional, R2000 and Advanced houses in Canada

Source: (NRCan, 1993)

The use of passive design can further reduce energy demand to make net-zero energy buildings

possible. The concept of a net-zero energy home (NZEH) is a progression in advanced building

technology where the building energy requirement is so low that over a year it is either able to

produce as much energy from on-site sources as it requires or it exports as much energy as it

requires to import (Pless and Torcellini, 2009). Other forms of net zero buildings are net zero

cost where the amount paid by the utility for exported renewable energy is equal to the amount

imported to from the utility over the year and net-zero emissions where enough renewable

energy is produced or purchased to offset emissions of all energy used by the building Pless and

Torcellini, 2009).

Passive design optimizes energy use and comfort of buildings for the local micro-climate

through architectural design, site planning, structural, building envelope and passive mechanical

features (Mikler, et al., 2008). According to Harvey (2006), to achieve net-zero energy, energy

intensity of new buildings would need to be reduced by a factor of four or five in OECD

countries and three to four in non-OECD countries compared to average existing buildings. Such

orders of magnitude in heating energy use over new housing and factors of 10 to 25 compared to

25

existing buildings are being achieved throughout Europe through the Passive House Standard

(Harvey, 2006). Heating requirements of less than 15 kWh/m2 and total energy consumption of

less than 42 kWh/m2 have been achieved cost-effectively under this standard (Harvey, 2006).

As of 2007, over 10,000 passive house buildings have been constructed worldwide (Fiest,

2007b). In the U.S. the passive house standard has been able to reduce energy consumption by

up to 90% and can be met at a premium of between 10 to 15% over a conventional house

(Klingenberg, et al., 2008).

Fiest (2007b) compared the life-cycle energy consumption of a conventional German house

constructed to 1984 standards, a low energy house, existing passive house, new passive house

and self sufficient passive house. The extra embodied energy in the passive house was found to

be almost double that of a conventional house. He found that after 30 years, the new passive

house would provide 75% lifecycle energy savings and the self sufficient house which included

solar PV with battery storage resulted in 50% savings compared to the conventional house. Over

80 years, the life cycle energy savings for the self-sufficient house was reduced to 65% while the

passive house still achieved 75% savings as the embodied energy (primary energy input (PEI))

remains significantly less than the operational energy consumption (cumulative energy input

(CEI)), Figure 3-2. Greater energy reductions in the self-sufficient house are hindered by the

high embodied energy of the PV and battery storage their 30 year replacement cycle (Fiest,

2007b). R-PEI refers to the primary energy intensity of components that require replacement

over the lifecycle such as solar thermal collectors which had a life of 30 years. The highest R-

PEI was for the self-sufficient solar house due to the periodic replacement of the battery which

was assumed to have a life of 10 years and PV system would have to be replaced every 20 years.

A grid tied PV system would replace the embodied energy of the battery storage with the energy

required to import electricity. Depending on the nature of the exterior power source this could

significantly reduce lifecycle energy consumption.

26

Figure 3-2: Comparison of cumulative primary energy consumption for 80 year lifecycle.

Source: Figure 1 (Fiest, 2007b)

The 14 houses from CMHC’s Equilibrium housing program are intended to demonstrate the

potential for- net zero energy housing in Canada. Two of the houses are the product of the Solar

Buildings Research Network (SBRN) which is a collaboration of 13 universities and 6

government agencies that researches in low energy buildings and solar technology. Building

energy modeling software used by some of the design teams were HOT2000 and esp-r while

renewable energy systems were modeled using Matlab, RETScreen and TRNSYS (Charron,

2007). The average annual energy consumption of the Equilibrium houses is predicted to be

between 4,500 to 7,500 kWh excluding the energy gained from solar thermal collectors (Table

3-3). The remaining demand is met primarily through PV systems. A potential drawback from

this is that if electricity demand is not significantly reduced and large PV systems are relied

upon, the NZEB may not offset peak demand such as late afternoons on hot summer days to

power air conditioning systems when the electricity fuel mix may be have a greater contribution

from carbon intensive sources (Pless, et al., 2009). Peak demand however is reduced by

measures including passive cooling through adequate shading, use of heat recovery ventilator,

thermal storage through enhanced thermal mass, better insulation and windows, improved day

27

lighting, use of ground source heat pump for cooling, energy efficient appliances and lighting,

and behavioural change through variable pricing (Pless, et al., 2009).

Table 3-3: Predicted energy consumption for EQuilibrium houses,

Load Energy Consumption (kWh/a)

Lighting, appliances & other plug loads 2,734 – 5,450

Domestic hot water 0 - 504

Heat recovery ventilators heating and cooling 250 – 1,750

Heating (solar thermal or GSHP) 500 – 2,000

Total 4,500 – 7,500

Source: Charron (2007)

3.2 Passive solar building design An extensive literature review was conducted of current building codes, research papers in low

energy building and case studies from the advanced houses to establish a reasonable basis for the

prototype house developed for this thesis. A comparison of current standards with low energy

building standards are presented in Table 3-4. Design guidelines by Charron, et al. (2006),

CMHC (1998), Chrias (2002) and detailed case studies from passive houses in the U.S. climate

Klingenberg, et al. (2008) are particularly practical sources of information on the development of

net zero energy houses. While climate will vary the overall influence of design parameters

generally, the advanced houses require almost double the insulation from current standards, 30 –

50% glazing on south faces that have low conductance and high solar heat gain factors with

minimal glazing other faces, sufficient thermal mass to store heat and avoid overheating, high

efficiency light fixtures and appliances, compact building form, a tight building envelope and a

heat recovery ventilator.

28

Table 3-4: Comparison of Building Characteristics that Influence Energy Use in

Construction Standards and Low Energy Building Designs Building Code

Ontario Building Code 2006

R-2000 (NRCAN, 2010)

Charron Design Guidelines (Charron, et al., 2006)

Passive House (Malinsani, et al., 2009)

Alstonvale

(Candanedo

, et al.,

2008),

(Athienitis,

et al., 2009)

SUI-NZEH (Gorgolewski, 2007)

Ecoterra (Athienitis, et al., 2009)

Location Ontario, < 5000 HDD

Canada Europe Germany

Hudson, QC Toronto, ON

Eastman, QC

Glazing

< 20% of the floor area of storey served & < 40% of total wall area.

South 7–12%, (20% with controlled blinds), North <4%, East <4%, West <2% of floor area.

South 50% max (+/- 45o from south), large, square to min. frame heat loss.

South 42%, East 7%, West 10% of wall area

South 16% of floor area

South ~40% of floor area

Wall Insulation

RSI 3.34 RSI >4.4 RSI 5 to 7 RSI >6.67 RSI 5.6 RSI 10.8 RSI 5.9

Basement Walls

RSI 2.11 Near full height

RSI 1.9 RSI 4.6 RSI 10.8 RSI 4

Ceilings RSI 7.00 RSI > 6.67 RSI 8.7 - 10.5

RSI >7.2 RSI 12 RSI 13.6 RSI 7.91

Slab On Grade

RSI 1.41 -1.76

RSI > 5 RSI 4.6 RSI 3.6

Exposed Floor

RSI 4.4 RSI 12

Doors RSI > 0.7 RSI > 1 Windows:

U Factor <

2.0 W/m2K,

RSI > 0.5

U <1.5 W/m2K, RSI 0.67

U Factor <

1.7W/m2K

SHGC >

0.55

U<0.8, SHGC > 0.5

RSI: 1.2, U: 0.833, SHGF: 0.57

U 1.4, RSI 0.71

RSI: 0.967, U: 1.03, SHGF: 0.6

Air Leakage

< 1.5ACH @ 50 Pa

<0.6ACH @ 50 Pa

0.5ACH @ 50Pa

0.8 ACH @ 50 Pa

HRV Efficiency

Min 55% > 70%, <1.5W /L/s

80% to 85% >75%, <1.44 W/L/s

29

Building energy demand is affected by numerous interdependent factors. Figure 3-3 illustrates

and classifies these factors as locational and environmental dependent variables that cannot be

modified and provide context for the building design. Design dependent variables are those

under control of the designer in response to both the location and environmental constraints, and

the functional requirements of the building. Finally, the building use and user dependent

variables define the energy use as a result of occupancy. These interactions and impact on low-

energy building design are discussed further in the following sections.

30

Figure 3-3: Flowchart of variables that influence building energy demand

Building Heating/Cooling Loads

Orientation & Location

Wind / Shading

Building Electricity Demand

Lighting Requirements

Building Electricity Supply

Hot Water Demand

Solar Thermal Solar PV

Building Heating/ Cooling Distribution

(Pumping, Fans Controls)

District Heating /Cooling System Smart Grid

Insulation

GlazingType & Coverage

Airtightnesss

Occupancy & Schedules

Building Envelope

Heating & Cooling Degree Days

Solar / Shading

Thermal Bridge / Thermal Mass

Passive Gains / Losses - Heating /

Cooling

Mechanical Ventilation

Water Demand

Appliances & Equipment

Excess Heat or Cooling

Water Supply

Wastewater Generated

Location and Environmental Dependent Variables

Energy Demand

Building Use & User Dependent Variables

Design Dependent Variables

Cladding / Roof

Energy & Water Supply

Building Heating / Cooling Supply

Distribution/Process

- Heat- Bio-methane

Legend

Internal Active Gains

31

Environmental and Location Dependent Variables

Environmental and location dependent variables such as climate (including important micro

climatic features such as fog, solar availability, heat island and wind), groundwater and soil

conditions, terrain, neighbouring buildings and shading features have significant impacts on

building energy use. These variables are unique for every site. Other subtle sub-optimal site

conditions such as noise, reflections from other buildings and views may also restrict design

options and building performance (Tombazis, et al., 2001). As areas surrounding the site develop

or neighbouring vegetation matures conditions can change such as solar availability can change

affecting the long term performance of the building. On the other hand, the site location can be

specifically selected for desirable environmental and location variables.

Ideally, buildings should be oriented due south however orientation within 22.5o is suitable

providing 92% of potential solar winter gain while maintaining effectiveness of awnings and

shading features (Erley, et al., 1979). Chiras (2002) however, recommends only 10-degree

deviation to minimise summer solar gain. Local climate conditions such as fog, temperatures and

air pollution can affect insolation by 20% (Galloway, 2004). Local morning fog for example may

warrant positioning solar collectors slightly west of due south so that diffuse radiation is

collected in the morning while direct solar gain is maximised in the afternoon hours (Erley, et al.,

1979). Time of day electrical pricing may also influence the desired orientation of the building

however, 95% of the solar fraction in solar thermal collector can still be obtained at 35 degree

from due south (Erley, et al., 1979).

Properly placed landscape features could also significantly reduce cooling loads. One tree per

house could provide cooling energy savings of between 17% - 24%, while adding three trees per

house could reduce cooling load between 17% - 57% (Santamouris 2001, Akbari, et al. 1992,

Athienitis, et al. 2002).

Climate Consultant 4 and HEED are free design tools that identify important design strategies

based on local weather data. Both analyse Energy Plus weather files that graphically display

climate data and recommend passive design strategies for the particular climate (UCLA Energy

Design Group, 2009). For Toronto, Climate Consultant describes the climate as very cold, dry

32

climate in the winter and warm, humid climate in the summer. Some climate specific design

recommendations are:

• Snug floor plan with central heat source, south facing windows, and pitched roof for wind

protection

• Local garages or storage areas on the side of the building facing the coldest wind to help

insulate

• Keep the building small (right sized) because excessive floor area wastes heat and

cooling energy

• Tiles or slate (even on low thermal mass wood floors) or a stone-faced fireplace can help

store winter daytime solar gain and summer night time “coolth”

• Use compact building form with square-ish floor plan and multiple stories to minimize

heat loss from building envelope (minimise surface to volume ratio)

• Provide high performance glazing (UCLA Energy Design Group, 2009).

Design Dependent Variables

Design dependent variables are those under the control of the building designer. Some of these

variables are informed by the intended building use while others should incorporate the

locational features. Architectural features should consider both of those constraints with the

objective to minimise energy consumption. Tombazis (2001) suggests passive dynamic design or

regarding the building as a living organism that is able to adapt to changing conditions. As such

it is able to maximise the available desired resources, protect the building from unwanted

influences and make up for deficient site layout and orientation (Tombazis, et al., 2001). Such an

approach is a diversion from a traditional architecture designed from space-function and

aesthetic point of view which is then integrated to comply with building regulations and

standards (Tombazis, et al., 2001).

Conventionally, building energy modelling is not conducted for residential buildings and the

impact of passive features and internal gains are neglected. Annual heating and cooling needs are

not quantified and heating and cooling systems are based on worst case scenario. Heating system

designs for residential buildings are based on 99% design dry-bulb temperature. Worst case

assumptions are made by omitting potential solar or internal gains and heat storage (ASHRAE,

33

2009). Cooling systems are designed based on the 1% dry-bulb temperature and mean coincident

wet-bulb temperature. Indoor design conditions are typically 24oC dry-bulb and a maximum

relative humidity of 50 to 65% for cooling and 20oC and 30% relative humidity for heating

(ASHRAE, 2009). This often results in over sizing of mechanical equipment which is both more

costly and would require more energy to operate. For passive design however, understanding

internal gains and solar gains is essential to designing a comfortable and economical building.

A well designed passive-solar-heated building may provide 45% to 100% of daily heating

requirements (ASHRAE, 2007). Passive solar buildings seek to maximise solar heat gains in the

winter and minimise them in the summer while maintaining indoor comfort year round. Chiras

(2002), recommends that buildings have a rectangular floor plans and length to width ratios

between 1.3 to 1.5 oriented along the east west axis to provide greater south wall exposure for

winter passive heating and minimise east-west exposure during the summer.

Heat loss should be minimised through minimising thermal bridges, providing advanced

insulation and minimising uncontrolled infiltration. Free energy is maximised through passive

solar heating during the heating season, passive cooling season and daylighting while

maintaining thermal comfort (Hastings, et al., 2007). The building should take advantage of the

surrounding climate and building components to maximize natural ventilation, day lighting,

heating and cooling thereby reducing the building’s overall energy consumption and the size of

mechanical equipment. This is accomplished by controlling heat transfer through radiation,

conduction and convention and thermal storage of the structure itself (Mikler, et al., 2008).

In the northern hemisphere south facing walls which can be net heat sources in the winter are

heavily glazed between 30 to 50% of wall area with windows that have low conductance and

high solar heat gain values. Glazing on the other faces is minimised as they typically provide net

heat losses in the winter and provide unwanted solar gains in the cooling season causing

overheating. South facing windows should have a solar heat gain coefficient (SHGC) of under

0.4 for hot climates, 0.4 – 0.55 for intermediate climates and greater than 0.55 for cold climates

(Chiras 2002, Charron, et al 2006). All windows should have U-factors of less than 1.7 W/m2K

and a certified air leakage rate of less than 1.5x10-4L/s/cm2 (Charron, et al., 2006).

34

That amount of glazing on the south wall depends on individual building characteristics, thermal

control systems and the local climate (Charron, et al., 2006). The effect of increasing glazing

area usually follows a U-shape curve where the benefits of increased glazing increases (although

with diminishing returns) up to a point where the night time heat loses in the winter and excess

solar gains outweigh the benefits of larger glazing areas (O'Brien, et al., 2009). Overheating is of

particular concern in October when the sun angle is low providing less shading from overhangs

and the ground is unfrozen (CMHC, 1998). CMHC (1998) recommends that temperatures do not

exceed 25oC for more than 4% of the heating season.

Thermal mass in a building can provide thermal storage to avoid overheating and regulate

temperatures enabling a higher proportion of glazing to be used however this must be balanced

by potentially increased heat loss when high solar gains are unavailable. For a typical residential

building, additional thermal mass is only required when glazing exceeds 6% to 7% of floor area

however, with 100 mm to 150 mm of thermal mass, 7 to 12% can be achieved and up to 20% is

possible with the combination of solar spaces, thermal mass and controlled shading (Charron, et

al. 2006, CMHC 1998, Chiras, 2002, Athienitis, et al. 2002). The optimal thermal mass depends

on the wall or floor composition material characteristics such as the self admittance which is

related to the thermal heat capacity, absorptivity of the surface, and conductivity of the section

(Charron, et al., 2006). Chiras (2002) recommends for the northern hemisphere, minimising

north and east facing glass to at most 4% of total floor space and west facing glass should be less

than 2% of total floor space. Based on 30 years of construction of passive solar buildings in

Vermont, Kachadorian (2006) found that generally east, west and south glazing should be

between 10% and 20% of the total exterior heated wall area. Additionally, the peak temperature

increase of the thermal mass in February should ideally be 4.5oC (8oF) (Kachadorian, 2006). A

minimum temperature of the thermal mass of 16.7oC and a maximum temperature of the thermal

mass of 21oC provide optimal occupant comfort (Kachadorian, 2006).

Window areas beyond 50% glazing however, provide little benefit in the amount absolute light

and result in reduced contrast and increase glare (Hastings, et al., 2007). Awnings ideally should

be designed to leave south facing windows un-shaded during the winter solstice when heating is

required and ideally fully shaded during the summer solstice when solar gains are unwanted.

35

Passive buildings are very tight having uncontrolled infiltration of 0.6 ACH (Klingenberg, et al.,

2008). Mechanical ventilation is therefore required to maintain adequate indoor air quality. The

minimum ventilation requirement according to Canadian standards is 7.5 L/s per person (NRCan,

2009g). The total required ventilation capacity is based on sum of the ventilation requirements

for each room in the house. The fresh air requirements for unfinished basements and master

bedrooms are 10 L/s. Other rooms require 5 L/s each (NRCan, 2009g). Ventilators typically

operate continuously at low speed operation 40 – 60% of the high speed capacity to ensure

removal of indoor pollutants and adequate fresh air. High speed operation is used only

occasionally in bathrooms and kitchens or when higher ventilation rates are required (NRCan,

2009g). Charron (2006) reports that heat recovery ventilators should have a seasonal

effectiveness ranging from 80% to 85%.

Electrical loads should also be minimized through the use of energy efficient lights, maximize

daylighting, automated controls and using energy efficient appliances. Any energy required to

condition the building should be recovered as much as possible (Charron, et al., 2006).

A sensitivity analysis tool is currently under development through the Solar Building Research

Network (SBRN) that is able to identify key design variables that are most influential in helping

to reduce building energy consumption helping to guide the design process more efficiently than

traditional trial and error approaches (O'Brien, et al., 2009). In their preliminary analysis of a

solar house based on a Toronto climate O’Brien et al. (2009) found that building energy

performance and the change in optimal glazing area was most sensitive to infiltration and

ventilation, HVAC set points and Internal gains, and moderately affected by airflow between

zones. Additionally maximum glazing area was also moderately affected by the number of

thermal zones (Table 3-5).

36

Table 3-5: Sensitivity of energy modelling parameters on building energy demand and optimal glazing

Factor

0-9 10-19 20+ 0-9 10-19 20+Ground Reflectance Infilt rat ion and Vent ilat ion Internal Gains Airflow Between Zones HVAC Set-points Therm al Mass Discret izat ion Num ber of Therm al Zones Window Trasm it tance External Shading

Average Change in Energy (%)

Maxim um Change in Opt im al Glazing Area (percentage points)

Source: Table 2 in O'Brien, et al. (2009)

Optimal glazing area is extremely sensitive to infiltration and ventilation with a higher optimal

glazing area with higher infiltration rates as solar heat gains become more usable (O'Brien, et al.,

2009). Internal gains from occupants, appliances, water heating and lights, decreases space

heating energy consumption. High internal gains would result in a lower optimal glazing to

prevent overheating however this would have less of an impact for houses with higher heat

losses (O'Brien, et al., 2009). Higher cooling set-point temperatures shifts the optimal glazing

higher as more solar gains can be absorbed before cooling is required. Modelling the building as

a single zone assumes the same temperature throughout the entire building resulting in larger

optimal glazing. Having at least three zones (basement, north side of house, south side of house)

is able to capture impacts of overheating in south facing rooms, provide more accuracy and

reduces the optimal glazing obtained (O'Brien, et al., 2009).

Charron (2007) developed a genetic algorithm optimization tool for net zero energy building that

accounted for building envelope, mechanical and solar energy systems based on optimal costs.

The optimal solution can vary significantly depending on climate, equipment costs and

government inceptives toward efficiency measures such energy retrofit rebates and feed-in tariffs

to support renewable energy.

Simulations for four distinct North American climates show the varying optimal solutions based

on local climate are shown in Table 3-6 (Charron, 2008). The optimal solution in this case would

37

provide the greatest energy reduction for the least cost, however this may not be the lowest

energy or GHG emission solution. In a NZEH that imports and exports energy with the electrical

grid, consideration should be given to the carbon emissions attributed to the external energy

source. In a grid that is heavily comprised of coal source energy a strategy to select appliances

can utilise thermal energy sources such as solar thermal, natural gas or biofuel (ranges, water

heaters, space heaters, etc.) would be a better strategy. On the other hand, where clean grid

energy exists, the use of efficient auxiliary appliances would be of greater benefit if they can

displace fossil fuel emissions such as natural gas and propane.

38

Table 3-6: Least cost optimal configurations of net-zero energy buildings in cities of

varying climates

Source: Table 2, (Charron, 2008)

Building Use and User Dependent Variables

User behaviour and occupancy may result in actual building energy use differing significantly

from that predicted in the building design.

While physical aspects of the building such as architecture, construction, orientation, appliances

and equipment and HVAC systems can reduce overall energy consumption; occupational aspects

including the number of people, hours of occupation, type of activity, plug loads and occupier’s

attitudes are much more difficult to predict (Matthews, 1987). Accounting for internal gains

becomes more important as buildings become more energy efficient as a smaller share of their

heating load is provided by the space heating system (Hodges, 1985). To provide consistency in

39

energy analysis, the R2000 Standard has developed standard operating conditions which are

based on two adults and two children living in a house 50% of the time (NRCan, 2005).

However, its assumptions on auxiliary energy demand and water demand are significantly

greater than what is possible with the latest energy efficient appliances. Gorgolewski (2007)

provides a discussion of some reasonable assumptions to reduce electricity consumption by 60%

and hot water consumption by 56%. A comparison between standard energy use and using

advanced energy efficient appliances is presented in Table 3-7.

Table 3-7: Comparison of electricity loads R2000 Standard operating condition versus

advanced energy efficient appliances. R2000 standard operating conditions Advanced energy efficient appliances Interior lighting 3 kWh/d 1 kWh/d Major and minor appliances 9 kWh/d 3.77 kWh/d Other plug loads 8 kWh/d 3 kWh/d Exterior use 4 kWh/d 1.85 kWh/d Hot water use 225 L/d 98.5 L/d

Source: (Gorgolewski, 2007).

3.3 Renewable Energy

3.3.1 Solar PV

Photovoltaics (PV) convert photons from beam and diffuse solar radiation to direct current

electricity. Electricity is generated when the energy from the photons is greater than the band gap

of the semiconductor to move electrons to the conduction band to generate electricity. Solar

photovoltaic cells (PV). The most common PV technologies Monocrystalline silicon (sc-Si) and

Polycrystalline (mc-Si) have efficiencies ranging from 12 to 18%, and Amorphous silicon (a-Si)

have efficiencies between 5 to 8% with the remaining energy produced as heat (Poissant, et al.,

2008). Monocrystalline and polycrystalline silicone cells are the most popular capturing 65% of

global market share in 2006 (IEA-PVPS 2007).

The performance of the PV system is largely dependent on slope and azimuth of the collectors,

local climatic conditions, the collector efficiency, and the operating temperature of the cells.

Unlike solar thermal collectors, solar PV relies on both direct beam radiation and diffuse

radiation. As a result high diffuse radiation from a bright white sky with light haze or fog can

40

increase PV output by 16% over a deep blue sky (Galloway, 2004). Overheating of PV panels

can have a significant impact on PV performance. PV performance can decrease by 0.4 – 0.5%

for every 1oC above its rated temperature (typically 25oC) (Conserval Engineering Inc., 2010).

Modules commonly heat up to 50oC resulting in a decrease in performance of up to 25%

(Conserval Engineering Inc., 2010). Figure 3-4 demonstrates the impact of temperature on

diminishing collector performance.

Figure 3-4: Effect of temperature on PV efficiency

Source: Figure 9.5 Galloway (2004).

Solar PV/T systems combine PV systems with solar thermal collectors to produce both power

and heat from the same area. The overall efficiency is increased because heat is removed from

the PV panel and typically used for space heating, solar hot water applications or condensing

chillers. Combined PV and thermal systems could increase solar efficiency to 80% while

providing savings in installation costs over two separate systems (Charron, et al., 2006).

41

PV systems are used in either on-grid or in off-grid applications (NRCan, 2004a). A typical on-

grid connects PV system consists of PV panels, a power converter, the grid, and energy demand

from the grid to use the exported energy. The power converter consists of an inverter that

converts direct current produced by the PV panels to alternate current, provides surge protection

and controls the power output to match that required by the utility and the home (Kemp, 2006).

Off-grid applications additionally include battery storage and a backup power source to ensure a

reliable power supply year round (Kemp, 2006). In an off-grid system, the inverter has the

additional function of diverting excess electricity once the batteries have been charged to a

diversion load such as a water heater to prevent overcharging (Kemp, 2006). In some off-grid

applications such as pumping water no battery storage is required as pumped water can be stored

and pumping can occur when solar energy is available (NRCan, 2004a).

Solar PV is typically the primary electricity source and has the largest capital costs of all

components in a NZEH. Therefore it is important that building and site conditions are optimised

to minimise PV system size and maximise the system’s performance (Kemp, 2006). Typical

capital costs in Canada are $10,000 / KW (Poissant, et al., 2008). Due to their high capital cost,

oversized systems needlessly increase the expense of the system.

The results of a study on the performance of a NZEH in Colorado found that PV production was

124% greater than the site energy consumption (Norton, et al., 2007). The over sizing was

attributed to user behaviour as 58% of electrical consumption was attributed to other electrical

loads (appliance and plug loads) (Norton, et al., 2007). While it is possible to monitor a family’s

electrical consumption and incorporate it into the design, consumption patterns would change

with time as family’s age and the design could be inadequate if the house is resold. However,

this difficulty could be overcome by future purchases of additional arrays and at the end of the

20 – 25 year lifecycle of a typical array (Kemp, 2006).

The tilt angle of the PV array will depend on the latitude of the location, the distribution of the

electricity load throughout the year, if snow accumulation is a factor, the existing angle of the

proposed mounting surface and the maximum allowable structural loads on a surface. The

orientation of the PV array will also be dependent on local climate conditions such as fog,

42

temperatures and air pollution that can affect insolation by 20% (Galloway, 2004), orientation of

the existing mounting surface (e.g. roof), and time of day electrical pricing (Erley, et al., 1979).

A typical rule of thumb is to mount the system at an angle equal to the latitude to balance both

winter and summer production (Kemp, 2006). Trackers can increase summer PV production by

up to 50% while winder performance improves by only 10 – 20% (Kemp, 2006). There are fewer

benefits to tracking at higher latitudes where their additional costs could be better invested in

additional panels (Kemp, 2006). Kemp (2006) recommends that panels have clear solar access

between 9 am to 3 pm. Panels are rated under ideal solar and atmospheric conditions and

typically at a temperature of 25oC (Kemp, 2006). Power production under actual conditions can

be 20 to 40% less and therefore should be de-rated accordingly (Kemp, 2006).

Modelling is typically conducted using typical meteorological year TMY files the latest version

TMY3 which represents representative weather from 1991 to 2005 weather record for 1020

locations (NREL, 2008). The data collected consists of hourly values for solar radiation, ambient

temperature, wind speed, wet bulb temperature, wind direction and cloud cover. Because this

weather data is from a limited number of discrete locations, local conditions may vary from those

at the nearest weather monitoring stations. Beyond the variability of actual annual weather

conditions from the TMY files, uncertainty in collector performance due to shading, snow cover

and temperature effects can also provide discrepancy between the predicted and actual collector

performance (Norton, et al., 2007).

3.3.2 Solar Thermal Systems

Solar thermal collectors use direct thermal rays for space and hot water heating. For residential

applications solar thermal collectors are typically used domestic hot water systems (SDHW) as

they have a year round heating demand however they are also used for heating swimming pools

and as part of hybrid thermal energy storage systems (Wong, 2007). Based on the average single-

detached residential building stock in Canada between 2003 and 2007, domestic hot water

consists of 16% of household energy consumption (NRCan, 2009a). In north-eastern United

States and Canada solar thermal collectors could provide 55% of domestic hot water demand and

35% in Canada’s arctic (Kemp, 2006). Greater reductions are possible if water demand is

optimized through water saving appliances and the use of a drain heat recovery system.

43

The system performance is dependent on the system characteristics, solar radiation available,

ambient air temperature, and the heating load characteristics (NRCan, 2004b). A typical solar hot

water system consists of a solar collector, circulating system to transfer heat from the collector to

the storage tank which stores preheated water and a backup water heating system such as an

additional storage tank or an instantaneous water heater run by natural gas or electricity (NRCan,

2004b). The most suitable choice for backup will depend on the carbon intensity of the electrical

grid (Norton, et al., 2007).

There are typically three types of solar thermal collectors: unglazed liquid flat-plate collectors,

glazed liquid flat plate collectors, and evacuated tube solar collectors (NRCan, 2004b). Unglazed

liquid flat plate collectors are typically used only in low temperature applications (between 20 oC

and 40oC) or where heating is only required during the summer time in colder climates since they

have high thermal losses in colder climates (NRCan, 2004b). They are the least expensive types

of collectors and are primarily used to heat swimming pools however, they could be suitable in

hybrid thermal energy storage situations. In such a situation the collectors would collect heat in

the summer to inject heat into either an aquifer or borehole thermal energy storage system for use

in the winter (Wong, 2007).

For solar domestic hot water and space heating applications, either glazed liquid flat plate

collectors, and evacuated tube solar collectors are typically used (NRCan, 2004b). Flat plate

collectors are able to heat water 50oC to 60oC, typical of what is required for domestic hot water

systems (Wong, 2007). Typical costs are $25 per square foot and have a life of between 30 to 40

years(Ramlow, et al., 2009). They are known for better snow shedding characteristics than other

collectors and are more rugged (Ramlow, et al., 2009).

Evacuated tube collectors allow for temperatures 60 oC and 80oC to be reached even in cold

climates (NRCan, 2004b), and are able to deliver heat at very low irradiance levels in the winter

and during overcast periods (Kovacs and Patterson, 2002). While higher temperatures can be

achieved with evacuated tube collectors most expensive and these systems can more easily

overheat in the summer. Evacuated tube collectors are at least three times as expensive ($75 per

square foot) and have the service life (15 years) than flat plate collectors (Ramlow, et al., 2009).

This is because the seal to maintain the vacuum inside the collector deteriorates with time

deteriorating the performance of the collector to that of a flat collector or worse (Ramlow, et al.,

2009). The high insulation of evacuated tubes makes them susceptible to snow accumulation

44

between the collectors and they are too fragile to scrape accumulated snow off (Ramlow, et al.,

2009).

Flat plate collectors are more efficient than evacuated tube collectors where the difference

between the inlet temperatures and the ambient air temperature is less than 21oC (70 oC), Figure

3-5 (Ramlow, et al., 2009). This makes flat plate collectors more efficient for all residential and

most commercial applications in addition to their lower costs, greater durability and longer life

(Ramlow, et al., 2009).

Figure 3-5: Mean collector efficiency ratings

Source: Figure 3.6 (Ramlow, et al., 2009).

Overheating of the thermal collectors is of significant concern as this can cause excessive

pressure within the circulation system and cause “collector stagnation” which breaks down the

antifreeze circulation fluid leaving sticky deposits within the plumbing components (Kemp 2006,

Charron, et al. 2006). As a result there are tradeoffs providing optimal tile for summer and

winter design conditions. Overheating can be avoided by increasing the tilt angle from the

optimal tilt angle or diverting the excess heat to supplement another heating load or thermal

energy storage. Thermal energy storage can be used to balance ground temperatures if a ground

source heat pump system is used or in a community energy system which could even out peak

loads and supply heat for building that do not have solar access (Hastings, et al., 2007).

45

Hastings (2002) recommends that for a large collector area overheating can be avoided if the

collector tilt angle is increased 35o beyond the optimal tilt angle for southern latitudes (latitudes

around 45o) and 50o for northern latitudes (latitudes around 50o). Façade mounted solar thermal

systems can avoid overheating while maximising thermal collection in the winter and avoid

snow accumulation (Hastings, et al., 2007), (Kovacs and Pettersson, 2002). Façade mounted

thermal collectors also can reduce the U-factor of the wall by up to 90% during cold winter days

with high irradiation and 45% during days with low irradiation due to the higher temperature

collector on the wall (Charron, et al., 2006), (Weiss, 2003). The range of collector area for a

typical residence is between 4 to 8 m2 (Charron, et al., 2006), (Weiss, 2003). For small systems 2

to 5 KW of heat load, the optimum storage volume is between 50 to 200 L/kW (Charron, et al.,

2006), (Weiss, 2003). Hastings (2007) recommend DHW systems be designed at 40o to 50o

slopes and for a single family house recommend a tank volume of 100 to 150 l/occupant and a

collector area of between 1.3 to 2.5 m2/occupant or 400 to 600L/house and 5 to 10 m2/house.

3.3.3 Ground Source Heat Pumps

Ground source heat pump systems (GSHP) utilise the solar energy stored by the ground or water

and its thermal mass to act to be a heat source in the winter and a heat sink in the summer. An

efficiently designed GSHP system can provide a coefficient of performance (COP) of between

3.0 to 4.0 meaning that on average for every unit of energy required by the heat pump 3 to 4

units of heating or cooling energy can be obtained from the system(Dickie, 2008). A GSHP

system consists of three components: the ground or water heat exchanger, the heat pump and the

distribution system.

Heat exchangers are typically based on the peak design conditions, either peak heating or peak

cooling loads whose design depends on the climate, hydrogeological conditions (subsurface

conditions, thermal conductivity and groundwater quality and flow) and the available land for the

heat exchanger (VEL Engineering; Hemmera Energy Inc., 2004).

The heat exchanger can either be a closed loop or open loop system. Ground heat exchangers can

be horizontal or vertical loops that circulate antifreeze in closed loops systems or groundwater in

open loop systems in the ground. During the heating season, the heat pump in the house takes

heat from the heat exchanger to heat the house dropping the temperature of the fluid. In a closed

46

loop system, the cooler fluid is heated up again to the earth’s temperature as it flows through the

heat exchanger in the ground and then is re-circulated to the heat pump. Closed loop systems can

consists either be vertical or horizontal heat exchangers. Vertical systems are installed in a series

of boreholes between 15 – 100 m deep and 10-12 cm in diameter (NRCan, 2002). Similarly,

horizontal heat exchangers consist of a closed circuit of pipes buried in a series of trenches 2 to

2.5m in depth (NRCan, 2002). In open loop systems, groundwater is pumped from a supply well

providing a flow and heat source for the heat pump at a rate suitable for heating the house. The

water from the heat pump is then expelled into a separate receiving well resulting in a

significantly smaller heat exchanger system. Surface water systems similar to ground systems

utilize the constant water temperature in bodies of water such as ponds and lakes to exchange

heat through open or closed loop heat exchangers with the heat pumps.

During the cooling season, the heat exchange process is reversed recharging the ground

temperatures with the heated fluid. This also provides a supply of “free” heat that could be used

to suppliant the domestic hot water systems. Inadequate spacing can cause thermal interference

between rows of trenches and boreholes reducing the overall system performance. CSA 448

requires that Long term performance can also be affected if systems have large differences

between the amount of heat extracted during heating mode and the amount of heat rejected

during cooling mode resulting permanent changes in local ground temperatures (Kavanaugh, et

al., 1997). In such cases, the system is unbalanced. An unbalanced situation could require a large

heat exchanger to extract the required heat over a larger area thus resulting in a more expensive

system with excess capacity in the alternate season. In commercial systems, balance is tried to be

achieved by matching heat pumps with zones within the building that have opposite building

heating and cooling loads maximising the use of the heat exchanger and overall system

efficiency (Kavanaugh, et al., 1997). A similar strategy could be applied in a community setting

by matching individual buildings that would be complementary heating and cooling needs (VEL

Engineering; Hemmera Energy Inc., 2004). A building could also be specifically designed to

minimise system imbalance. Alternatively, a hybrid system such as using solar thermal collectors

to recharge the ground to maintain stable ground temperatures or cooling towers to waste heat to

the atmosphere could be used to deal with system imbalance (VEL Engineering; Hemmera

Energy Inc., 2004).

47

For climates with significant solar availability in the summer, relatively low cooling

requirements and high heating requirements a thermal energy system (TES) could be more

effective than a conventional GSHP system. A TES system uses heat collected from solar

thermal collectors in the summer or waste heat sources to raise the temperature of the ground or

aquifer like a battery. As in a conventional GSHP system, heat is drawn from the ground heat

exchanger but at higher than temperatures resulting in a more efficient system. Integrated in a

community energy system, groups of buildings can create a large thermal mass from multiple

heat sources thus maximising the heat production and use in the community.

The distribution system can either be a forced air or a hydronic system. In a forced air system a

heat pump is able to heat the air flowing through the heat pump by between 10oC to 15oC while

in a hydronic system the heat pump will supply water at a temperature of up to 50oC.

48

4 Methodology This chapter begins with a discussion about the development of the low energy detached house

and townhouse models and their characteristics. This is followed by introducing the passive

community model and two density scenarios studied for each building type. Finally, the total

building energy demand is presented in each of the scenarios demonstrating the impact of

restricted solar access on heating and cooling loads.

Two building scenarios of varying densities in a 16 ha neighbourhood are studied. Scenario 1

consists of detached houses and scenario 2 consists of row houses. Both housing types and

neighbourhood design are based on building and community passive design strategies. A low

energy building model representative of a passive single-family house and row house is

developed to provide a variation in density and set the energy demand/unit. The building

characteristics will also provide the spatial constraints such as available roof area and building

height and width which determines the building spacing and the density of the development. The

spacing between buildings is based on the desired solar access in the scenarios presented in

Section 4.3.

The potential energy supply from waste and solar energy is then established based on the

community metabolism and spatial characteristics of the scenarios.

4.1 Low-Energy building model

The low-energy buildings are located in the City of Toronto at 43.67N longitude and -79.63E

latitude. The average annual heating degree days are 3,870oC-days and the cooling degree days

are 1,167oC-days. The minimum daily mean horizontal solar radiation is 1.18 kWh/m2/d in

December and maximum in July at 6.18 kWh/m2/d (RETScreen). The average annual wind

speed is 4.2 m/s and most severe in the winter approaching from the south-west (RETScreen).

The townhouse and detached house models were developed based on passive design principles

described in Chiras 2002, CMHC 1998, Charron et al. 2006, Hastings et. al 2007, Galloway 2004

and case studies reviewed in Table 3-4.

49

The two buildings are illustrated in Figure 4-1 and Figure 4-2 and a summary of the building

dimensions and characteristics is presented in Table 4-2. Both buildings have the same floor

area, 185m2 with no basement. In the detached house, the floor space distributed across two

storeys while in the townhouse the floor plan is distrubted across three storeys. The occupancy in

both houses is assumed assumed to be two adults and two childern, equivalent of that used to

evaluate the Energuide rating for houses (Lee, R.K., 2007). Common floor area and occupancy

in both cases provide equivalent functional units of both area and occupany in comparing energy

use among the scenarios. This reduces the impact of value differences that may exist among the

different building types because they both provide the same utility.

Chiras (2002) reccomends that passive buildings have aspect ratios between 1.3 and 1.5. This

provides a dominant facade for south facing windows allowing high south facing window to

floor area ratios to be met. Retscreen simulations of the upper and lower recommended range

found that the more compact form, aspect ratio 1.3 is slightly more energy efficient than the 1.5

aspect ratio for a hypothetical house in Toronto. This could be because the compact form has less

north facing wall and a greater thermal mass than the longer form. The ideal ratio likely varies

with climate with a more compact form desirable in very cold climates with fewer sunny days

during the heating season. Thus the buildings are designed with an aspect ratio of 1.3 width to 1

depth oriented to the south. An unconditioned single car garage nested below the second floor

and attached to the west side of the house. The attached garage also provides a buffer for the wall

and floor attached to the house and shelters part of the western wall of the house from wind.

The roof pitch is 45o to distribute available solar energy for PV and thermal applications more to

the winter when it is most required. This also increases the availability of the solar system as it is

less likely that there will be snow accumulation at steeper angles and mitigates overheating of

the thermal collectors in the summer.

50

Figure 4-1: Detached house model: South-east view (left), North-west view (right)

Figure 4-2: Townhouse model: South-east view (left), North-west view (right)

The conditioned spaces were divided into 4 zones, a north and a south zone for each floor to

evalute indoor comfort levels. Thermal mass was provided by 100 mm concrete floor slabs.

Glazing was emphasized on the south side of the buildings and was allocted to similar proportion

in both buildings, 36.5% of south facing wall for the detached house and 37.3% of the south

facing wall for the townhouse or 11.2% south glazing of total floor area for the detached house

and 13.8% of south glaizng to floor area for the townhouse. The south glazing was also

distributed among the floors to so that they have proportionatey simliar glazing with respect to

the floor area so that one floor is not over glazed while the other is under glazed. For other

facades, glazing was limited to within the range recommended by Chrias (2002) of less than 4%

glazing to total floor space for north windows and less than 2% glazing to total floor space on

51

east. No glazing was provided on the west side of the house. In a neighbhourhood context, east

and west facing glass have even less value than a building in isolation since they are typically

shaded by adjacent buildings. The glazing consists of triple glazed low-e argon filled windows

with fiberglass frames which provide solar heat gain coefficient of 0.579 and heat loss

coefficient of 1.058 m2K/W, meeting the glazing specifications for cold climates recommended

by Chiras (2002).

South facing windows have awnings so that the windows are completely un-shaded on

December 21 and fully shaded on June 21. The awning dimensions were determined using the

online overhang design tool by Sustainable by Design (http://www.susdesign.com/overhang/).

Energuide standard conditions for lighting and appliance loads are 24 kWh/day (Lee 2007).

However, calculations of energy and water saving appliances by Tse, et al., (2009) for a similar

size net-zero house in Toronto demonstrate that total electricity loads can be reduced to 7.77

kWh/day by using the most energy efficient lights and appliances. Typical hot water usage in

Canada is 225 L/day at a temperature of 55oC. Tse, et al., (2009) also found that this demand

could be conservatively reduced to 100 L/day through water saving appliances. The specific

energy consumption for major appliances is based on average annual energy consumption

published by NRCan (2005) and presented in Table 4-1. The most energy efficient major

appliances were selected resulting in an average interior load of 3.77 kWh/day. The clothes dryer

was not considered to contribute to the internal heat load as it was assumed to be vented outside.

Table 4-1: Major energy efficient appliances selected (NRCan 2005). Appliance type Appliance model Specific energy consumption (kWh/year) Refrigerator GE Monogram 48” (includes freezer) 592 Stove Frigidaire BFEF323C* 438 Clothes washer Whirlpool WFW8500SR 152 Dishwasher Asko D3531 194 Clothes Dryer Miele T9800 438

Source: Table 4.6, Gorgolewski (2007)

Minor appliances were assumed to consume 3 kWh/day through the use of electronics and small

appliances with low standby and active standby power demands. This represents a 62.5%

reduction from the 8 kWh/day assumed in HOT2000 for use in the average household and found

to be reasonable based on a comparison of appliances and their min and mean consumption by

52

Fung et. al. (2003), presented in Gorgolewski (2007). Lighting consumption was assumed to be 1

kWh/day through the use of compact fluorescent bulbs, a 66% reduction from HOT2000 lighting

requirements (Gorgolewski, 2007). The daily energy consumption of electric appliances was

then assigned to schedules to distribute the internal heat gain throughout the day. The daily

energy consumption and heat gain for the refrigerator was evenly distributed for the entire day.

Major appliances such as the clothes washer, dishwasher and stove were lumped together and

gains were distributed for 5 hours per day, 2 hours in the morning and 3 hours in the evening.

Lastly, minor appliances and lights were lumped together and were assumed to operate over 11

hours in a day, in the morning between 6:00 and 9:00 and in evening from 16:00 to 23:00.

Natural ventilation is available between April 15 and Oct 15 to cool the buildings during

occupancy when the outside temperature is cooler then the inside temperature. The heating

system was assumed to have COP of 1.0 so it could be easily equated to the supply required from

various fuel sources. A high efficiency air conditioning unit with a COP of 3.5 was also

considered. However, a geoexchange system could reduce heating demand by at least a factor of

3 and obtain cooling COP of 4.0 (NRCan, 2002).

53

Table 4-2: Building characteristics Detached House Townhouse Number of stories 2 3 Floor area (m2) 185 185 Width (m) 11.7 9.5 Depth (m) 9.0 7.3 Total building height (m) 10.5 12.3 Roof area (m2) 179 121 Thermal resistance values: Exterior wall Ceiling Slab on grade Exposed slab Door

7 W/m2K 12 W/m2K 2.5 W/m2K 7 W/m2K (slab above unconditioned garage) 1.14 W/m2K

Thermal mass 1st & 2nd floor 100 mm concrete slab Window type Triple glazed, low-e, argon (U=1.058 m2K/W, SHGC=0.579) with fibreglass

frame. Size and number of windows: North South East West % South lazing of floor area/ south wall

4 @ 1.2m x 1.2m 8 @ 1.5m x 1.5m 2 @ 1.2m x 0.9m 0 11.2% / 36.5%

3 @ 1.2m 10 @ 1.5 x 1.5m 0 0 13.8% / 37.3%

Shading Strategy Fixed awnings 0.3 m offset and 0.9 m projection. Occupants 2 Adults and 2 Children occupied from 16:00 - 9:00 Set point temperatures Heating set point 21oC, cooling set point 24oC: Schedule: 6:00 – 9:00, 16:00 –

23:00 Heating setback 19oC, cooling set back 26oC, Schedule: 9:00 – 16:00, 23:00 – 6:00

Internal loads: Major appliances Minor appliances Indoor lighting Exterior loads

Energy efficient based on Tse, et al., (2009). 3.77 kW/day, schedule: refrigerator 24hrs; dishwasher, stove, washer, schedule: 6:00 – 8:00, 17:00 – 20:00 3.0 kW/day, schedule: 6:00 – 9:00, 16:00 – 23:00 1 kW/day, schedule: 6:00 – 9:00, 16:00 – 23:00 1.85 kW/day, result in no internal gains

Heat recovery ventilator 88% apparent sensible effectiveness @ 60 L/s, operating at 36L/s. Air change rate 0.6 ACH @ 50Pa Natural ventilation for cooling Available April 15 - Oct 15, set point 22oC. Domestic hot water load 100 L/day with water efficient appliances based on Tse, et al., (2009) Heating and cooling Auxiliary heating with COP 1.0, fan distribution efficiency of 80%. Central air

conditioning with COP of 3.5.

4.2 Passive Community Model

The passive community model consists of houses arranged in a grid pattern over a 16 hectare

area (400 m x 400 m) with parallel streets running east to west. All houses have full southern

exposure. The study area size was selected to represent a development with a sufficient scale to

evaluate changes, material flows, energy supply, and energy demand among varying densities.

Potential mixed uses could be located nearby the development to reduce transportation energy

54

use. The study area is assumed to be flat, free from vegetation and there are no obstructions

surrounding the development to impede the solar access on the subject plot. The setback between

detached houses in the east-west direction is 1.2 m. Attached row-houses run continuously in the

east-west direction.

The minimum house spacing was determined by the shadow projection from the top of the house

on the south side of the street to the bottom of the first floor window of the house located on the

north side of the street. The position of windows is as relevant as the building height in assessing

passive solar availability. Windows positioned higher allow higher densities, whereas windows

or glass doors positioned closer to the ground will have lower densities. In both buildings,

ground floor south facing windows were positioned 0.9 m from the ground. Passive solar design

guidelines recommend that buildings are ideally unshaded between 9:00 am to 3:00 pm solar

time on Dec. 21 or at minimum between 10:00 and 2:00 pm (Chiras, 2002).

The required spaced to obtain a given solar access is determined by projecting the solar altitude

and azimuth along the plane perpendicular to the rows of houses. The solar time, altitude and

azimuth were obtained using the online sun angle tool from Sustainable by Design

(http://www.susdesign.com/sunangle/) for the particular study location and time of year of

interest. The neighbourhood scenarios were oriented due south and used Equation 4-1 to

determine the minimum spacing between buildings.

Equation 4-1: Determining the minimum spacing between buildings

𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑆𝑝𝑎𝑐𝑖𝑛𝑔 =𝐻

𝑐𝑜𝑠𝛽× tan𝛼 − �

𝐷2�

Where, H = Total building height in front of building analysed β = Solar Azimuth α = Solar Altitude D = Depth of building in front of building analysed including overhang

The building spacing is highly dependent on the geometric characteristics of a building. Modest

changes in the total building height result in proportionately much greater changes in building

spacing. Two important geometric properties is the height of the windows and the roof slope.

Since almost all of the solar heat provided in a solar house is provided through the glazing, the

55

spacing can be reduced by leaving the bottom of the window sill unshaded rather than the entire

building wall. Therefore, the dimensions and height of windows in the neighbourhood context

are just as important as the proportion of glazing on each face of the house.

The roof slope dictates the overall building height. Some tradeoffs can be identified between

maximising roof area and solar radiation in the winter with a larger roof angle and reducing

building height to achieve higher density.

Figure 4-3 and Figure 4-4 show the relationship obtained between spacing and increased hours of

solar access for each of the studied building types with windows located 0.9 m from the ground.

Most important is the trend of spacing required to maintain unobstructed solar access increases

disproportionately with increasing hours of solar availability. This is because earlier in the

morning and later in the afternoon, the sun is further toward the south-east and south-west

resulting in longer shadows. The impact of the sun climbing in the sky and rotation toward the

south also means that spacing designed for early morning will not provide proportionately higher

solar heat gains. Between 8:30 am and 9:00 am, the required spacing decreases by 15 m and

provides only an hour of additional solar access whereas between 9:00 and 10:00 the spacing

only decreases only 7 m for an additional two hours of solar access.

56

Figure 4-3: Building spacing as a function of unobstructed solar access from different times of the day on Dec. 21 for the detached house

Figure 4-4: Building spacing as a function of unobstructed solar access from different times

of the day on Dec. 21 for the townhouse

0

1

2

3

4

5

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8

9

0.0

20.0

40.0

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8:00 8:30 9:00 10:00 11:00 12:00

Hour

s

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ing

(m)

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Detached House: Density vs. Solar Hours

Required Spacing (m)

Hours of Unobstructed Solar Access (hrs)

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Hour

s

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ing

(m)

Time

Townhouse: Density vs. Solar Hours

Required Spacing (m)

Hours of Unobstructed Solar Access (hrs)

57

In order to evaluate the sensitivity of building energy use with density two main scenarios for

each housing type were considered:

• Scenario 1a: All detached houses spaced based on solar noon. • Scenario 1b: All detached houses spaced based on 9:00 am solar time. • Scenario 2a: All row-houses spaced based on solar noon. • Scenario 2b: All row-houses spaced based on 9:00 am solar time.

Shading components equal in dimension to the simulated building and spaced according to the

scenarios were then modeled in DesignBuilder, Figure 4-5. A summary of the number of units,

population, density and roof areas for each scenario are shown in Table 4-3. The total population

is based on the building design conditions of 2 adults and 2 children per household.

Figure 4-5: Rendering of the neighbourhood scenarios evaluated. Scenario 1, detached

housing (top) and Scenario 2, row housing (bottom)

58

Table 4-3: Community characteristics Scenario 1a Scenario1b Scenario 2a Scenario 2b Minimum Spacing (m) 17.5 31.2 22.4 38.5 # of rows in east –west direction 28 28 41 41 # of columns in north-south direction 15 10 13 8 Total # of units 420 280 533 328 Density units/ha 26.3 17.5 33.3 20.5 Total Population 1,680 1,120 2,130 1,310 Population Density cap/ha 105 70 123 82 Total Roof Area (m2) 75,100 50,000 95,200 58,600

59

6 Results

6.1 Building Energy Demand Building energy demand is a product of both building and community characteristics described

in the previous sections. Building energy simulations using DesignBuilder modelled the

buildings’ the energy demand and comfort conditions. The buildings were initially modeled in

isolation then modeled among shading components of similar dimension to determine building

energy usage in each of the neighbourhood scenarios.

In addition to modeling the impacts of shading, model reflections can have a significant impact

on solar gains (DesignBuilder, 2009). Simulations for the detached house generally found,

heating loads were 28% higher when ground reflected solar was not accounted for. Cooling loads

only decreased by 1.3%. Therefore, the impact of ground reflectance is very significant to the

results. The proportional impact of ground reflectance did not change among the scenarios. This

is unintuitive because some sensitivity to shading for neighbouring buildings, which would cause

a reduction in ground reflectance should have been present. The author is uncertain why this is

not the case.

A solar domestic hot water (SDHW) system was modeled using RETScreen energy analysis

software. The system was designed to supply a daily hot water load of 100 L at 55oC. Based on

the daily demand, the system consisted of a Thermo Dynamics G32-P 3.0 m2 roof mounted flat

plate solar collector with a 160 L storage tank. This system provides 1.3 MWh of heating, 63%

of the annual hot water requirements. A secondary tank and heat source is required to provide the

remaining 900 kWh.

The results of the building energy models are presented in Table 5-1 and Table 5-2. All scenarios

approach the passive house requirements of 15 kWh/m2 for heating and cooling. Total primary

energy use is also well below 120 kWh/m2 total energy use passive house threshold. The

detached houses have 15% and 17% higher energy demand than the townhouses for the a and b

scenarios. In the isolated cases however, the total energy consumption varied by 4%. The

difference in total energy demand among the isolated buildings is likely so small because the

60

space heating and cooling demand make up a much smaller proportion of the total energy

demand than in the neighbourhood scenarios. Despite scenario b receiving at least 6 hours of

unobstructed solar access in the winter, space heating was 46% higher for the detached house

and 23% higher in the townhouse when compared to the isolated house. Scenarios a which

provide unobstructed solar access for only solar noon on Dec. 21 showed only a 12% increase in

heating energy consumption for the detached house and 10% increase in energy consumption in

the townhouse when compared with the less dense scenario b.

Figure 5-1 and Figure 5-2 show the impact of density on internal gains for each scenario. Solar

gains provide the dominant heat source for the houses with 41% for the dense scenario to 49%

for the isolated house. Internal gains from occupancy and auxiliary sources provide 38% to 41%

of the total heat load. Therefore proper modeling of auxiliary devices and occupancy are as

important as the impact solar gains. Unfortunately, occupancy and auxiliary devices rely on

individual behaviour and are far more difficult to predict.

Table 5-1: Annual household energy demand scenario 1

Isolated Scenario 1a Scenario 1b kWh/m2 kWh/hh kWh/m2 kWh/hh kWh/m2 kWh/hh Space Heating 10.1 1,870 16.5 3,050 14.7 2,730 Water Heating 4.86 900 4.86 900 4.86 900 Appliances 18.3 3,380 18.3 3,380 18.3 3,380 Lighting 1.97 365 1.97 365 1.97 365 Space Cooling 1.3 241 0.97 179 1.06 196 System Fans 1.44 267 1.17 216 1.26 233 Total 38 7,030 43.7 8,090 42.2 7,800

61

Figure 5-1: Scenario 1 internal gains

Table 5-2: Annual household energy demand scenario 2 Isolated Scenario 2a Scenario 2b kWh/m2 kWh/hh kWh/m2 kWh/hh kWh/m2 kWh/hh Space Heating 7.64 1,410 10.2 1,900 9.35 1,730 Water Heating 4.86 900 4.86 900 4.86 900 Appliances 18.3 3,380 18.3 3,380 18.3 3,380 Lighting 1.97 365 1.97 365 1.97 365 Space Cooling 1.33 245 0.98 182 1.04 192 System Fans 1.4 259 1.16 215 1.21 225 Total 35.5 6,560 37.5 6,940 36.7 6,790

-2000

-1000

0

1000

2000

3000

4000

5000

Auxillary Occupancy Solar Sensible Heating

Sensible Cooling

Inte

rnal

gai

ns (k

Wh)

Isolated

Scenario 1a

Scenario 1b

62

Figure 5-2: Scenario 2 internal gains

Additional simulations were conducted to evaluate the extreme impacts reduced solar access on

heating and cooling demand, Figure 5-3. For the detached house the building spacing in the

extreme case was half of scenario 1a, 8.75 m to yield a density of 40 units/ha. For the townhouse

the building spacing in the extreme case was half of scenario 2b, 11.2 m to yield a density of 50

units/ha. To provide consistency and evaluate the sensitivity of density with heating and cooling

loads an additional simulation had to be run for the detached house shaded by houses to the east

and west but unshaded to the north and the south. The isolated detached house case did not

consider any adjacent buildings and is therefore plotted separately. The results as expected show

that heating loads increase with density as solar availability decrease. Decrease in cooling loads

is only minor as awnings are already designed to reduce potential overheating in the cooling

season. The exponential shape of the heating curve shows a point between where increasing

-2000

-1000

0

1000

2000

3000

4000

5000

Auxillary Occupancy Solar Sensible Heating

Sensible Cooling

Inte

rnal

gai

ns (k

Wh)

Isolated

Scenario 2a

Scenario 2b

63

density does not significantly increase building heating demand and where increasing density

sharply increases building heating demand. These points are unique to each building and climate

location. In the figure the points are at approximately 26 unit/ha for the detached house and 32

units/ha for the townhouse. If transportation energy decreases with density an optimal density

between building energy use and transportation energy could be determined.

Figure 5-3: Heating and cooling requirements based on density

6.2 Urban Metabolism The community characteristics defined by the density scenarios developed in Chapter 5 were

used to determine the neighbourhood metabolism. The total community energy demand

calculated based on the number of units and building type are shown in Table 5-3.

Table 5-3: Energy Demand Scenario 1a Scenario 1b Scenario 2a Scenario 2b

SDHW (MWh) 546 364 640 426

Space Heating + Supplemental Hot Water (MWh) 1,660 1,020 1,490 863

Space Cooling (MWh) 75.0 55.0 96.8 62.9

Auxiliary Energy (MWh) 1,420 946 1,800 1,110

0

5

10

15

20

25

0 10 20 30 40 50 60

Ener

gy D

eman

d (k

Wh/

m2 )

Density (units/ha)

Detached Heating

Detached Cool

Isolated Detached Heating

Isolated Detached Cooling

Townhouse Heating

Townhouse Cooling

64

The solid and liquid residential waste flows through the community are presented in Table 5-4.

Residential solid waste flows through the community were based on a waste audit study

conducted by the City of Toronto in 2008. The audit found that for single family home, the

annual average household waste was 874 kg/household. Of that, 22% is reported to be residual

waste, 39% is compostable organic waste and 39% is recyclable (City of Toronto Solid Waste

Management Services 2008).

The daily indoor water demand in single-family households in Toronto is 320 L/capita (City of

Toronto 2002). Of that, 11% is due to leaks. The remaining demand is split between the clothes

washer, bath/shower, faucet, dishwasher and toilet. If reductions are possible proportionate to

those for hot water requirements excluding losses due to leaks, the total water demand could be

reduced to 160 L/capita. Assuming similar figures for wastewater, the actual volume to the

wastewater treatment plant would be 144 L/capita or 576 L/household. Table 5-4 shows the

resulting neighbourhood waste streams.

Table 5-4: Mass content of waste streams per year Waste Type Kg/Capita

(Kg/unit) Scenario 1a

(kg) Scenario 1b

(kg) Scenario 2a

(kg) Scenario 2b

(kg) Compostable 86 (345) 145,000 96,600 184,000 113,000

Residual 151 (191) 80,200 53,500 102,000 62,600

Recyclable 85 (338) 142,000 94,600 180,000 111,000

Wastewater 140 (560) 85,800,000 57,200,000 109,000,000 67,000,000

6.3 Energy Supply Potential Although there are numerous clean energy technologies available, this study will look at those

technologies that can be produced in the neighbourhood locally such as solar PV or source from

potential wastes that flow through the neighbourhood. The objective is to demonstrate that at

higher densities, less solar energy is available on a per capita basis; however, demand also

decreases while the mass of content and potential energy on the neighbourhood scale would

increase. Because solar PV is intermittent and energy from waste may not necessarily be

produced on site the objective is for enough potential energy to be produced to displace the

demand from the community. PV would ideally supply a surplus of electricity for dwellings that

may not be able to produce their own energy. A geothermal system could be extended to

65

community energy systems, however this would be only beneficial in neighbourhoods with

diverse heating and cooling demand to maximize use of the installed capacity. A similar problem

occurs with solar thermal systems which tend to have excess heat capacity in summer and would

require load diversity or thermal energy storage to maximize the utility of the energy. The

suitability of certain technologies in a district system and costs is discussed in greater detail in

Wilson, (2007).

6.4 Solar PV Fixed roof-top solar collectors were selected for south facing roof areas. It is assumed that 90%

of this area suitable for PV panels excluding the area required for the SHDHW system.

RETScreen Clean Energy Production Analysis software was used to calculate the total potential

energy produced. A Sanyo mono-Si solar panel with 17.4% efficiency was selected because of

its above average efficiency and that it is readily availability in Canada. The assumed inverter

efficiency was 95%, miscellaneous losses to account for snow cover, debris accumulation and

maintenance were assumed to be 12%, along with and an additional 5% losses during power

conversion were included (Myrans, 2009). Since solar access was not restricted on roofs in the

scenarios PV production varied only by building type. Also since PV did not displace heating

loads, the proportion of electricity met by PV was similar among the building types (aside from

minor variations in cooling loads). Both building types are able to produce more than enough

electricity to meet their demands from solar PV. The townhouses have 30% less collector area

per unit, than the detached houses. On a neighbourhood scale however, PV production was

related more with density than directly with individual roof area. PV production in the

townhouse scenarios was only 20% less than in the detached house scenarios over the entire

neighbourhood area due to a higher number or roofs in the townhouse scenario than in the

detached scenarios, Table 5-5.

66

Table 5-5: Neighbourhood PV Production Scenario 1a Scenario 1b Scenario 2a Scenario 2b Collector area per dwelling 80.4 80.4 54.4 54.4 MWh per dwelling 15.5 15.5 10.5 10.5 MWh total neighbourhood 6,510 4,340 5,600 3,440

6.5 Waste

The use of waste as an energy source maximizes the use of a resource that otherwise would be

wasted as well as provides a potential revenue source for a municipality (Corps, et al. 2008).

Municipal solid waste can be used to produce energy through methane capture at the landfill

from anaerobic decomposition of organic matter or incineration, pyrolysis or gasification to co-

generate heat and electricity (Harvey 2010a). Separation of recyclables and compostable

organics from residuals allows for wastes to be matched with the most appropriate energy

recovery methods. Recyclables themselves require less energy to produce the same material from

raw material and thus have far greater value than if used for energy generation processes (Harvey

2010a). Recovering energy from waste is especially valuable because it can provide a constant

energy supply unlike other intermittent energy sources. The maximum energy extracted from a

material is generally provided through co-generation. Residual waste that cannot be recycled or

decomposed can be incinerated. The overall energy recovery can be low if the waste stream

contains many components that yield no energy value or contain a large water content which

reduces the overall energy potential. Efficiencies for co-generation have been reported to be

between 22.6% and 45.2% for heat extraction and 25% to 29% for electricity production (Harvey

2010a). Table 5-6 shows the energy content calculated based on the residual waste values

calculated earlier and overall potential energy production. The higher heating value (HHV) is

used as it is assumed that the latent heat of condensation is captured by the cogeneration (Harvey

2010a). The energy production is conservatively based on the lower efficiencies, 22.6 % for heat

extraction and 25% for electricity production.

67

Table 5-6: Energy content of residual solid waste stream Waste Type HHV

(MJ/kg)~ % In Residual Waste Stream-

Energy Content (MJ) Scenario

1a Scenario

1b Scenario

2a Scenario

2b Paper 13.1 2 21,000 14,000 26,700 16,400 Plastic 33.5 18 484,000 322,000 614,000 378,000 Other Materials /w Heating Value^ 10 25 201,000 134,000 255,000 157,000 Other Materials w/o Heating Value 0 65 0 0 0 0 Total 705,000 470,000 895,000 551,000

~ Source: Reported in (Harvey 2010a), data from tables A3.36 and A 3.37 of EC (2001) Reference Document on Best Available Techniques in the Glass Manufacturing Industry, www.eippcb.jrc.es/pages/FActivities.htm. - Source: (City of Toronto Solid Waste Management Services 2008). ^ Household special solid waste.

Solid organic waste can either be diverted to a biogas digester to produce methane for vehicles or

to produce combined heat and power. The total potential energy produced depends on the

composition of the feedstock however, organic kitchen waste is particularly a very high energy

feed stock (Wong, 2007). Typical heat values of biomass are between 18 and 20 MJ/kg in which

a specially designed digester can produce methane gas with an energy content of 10 MJ/kg

(Harvey 2010b). The methane gas could be used for cogeneration of heat and power.

Combustion of methane gas in a combined heat and power boiler can yield 60 – 90% net

efficiency for systems between 0.1 – 1 MW with common electrical efficiencies of 30-40%

possible (Harvey 2010b). Therefore, an energy content of 10 MJ/kg for organic solid waste and

30% electrical production efficiency and a 70% overall efficiency was assumed.

For wastewater, biogas from anaerobic digestion can produce a net efficiency of 10-15% for

electricity production in addition to producing low grade heat (Harvey 2010b). The energy

content in Toronto’s municipal wastewater is 1.0 GJ/capita (City of Toronto Solid Waste

Management Services 2008). This number was proportionately scaled 0.45 GJ/capita to represent

reduced demand per capita from water efficiency measures. Thus, the resulting potential energy

from waste sources is presented in Table 5-7.

68

Table 5-7: Potential energy production from waste sources Scenario 1a Scenario 1b Scenario 2a Scenario 2b Residual Solid Waste Heat (MWh/year) 66.4 44.3 84.3 51.9 Electricity (MWh/year) 52.9 35.3 67.1 41.3 Organic Solid Waste Heat (MWh/year) 161 107 204 126 Electricity (MWh/year) 121 80.5 179 94.3 Wastewater Electricity (MWh/year) 26.3 17.5 33.3 20.5

69

7 Conclusions This thesis provides a quantitative analysis of the relationship of the impact of density on

building energy demand and potential energy supply from surfaces and flows through the

community. Passive design and energy efficiency measures were able to achieve overall energy

consumption between 77% and 82% less than the average Canadian single family house. Energy

consumption at the neighbourhood scale was 15% to 19% greater for the detached house and

3.5% to 5.7% greater for the townhouse than when modeled in isolation. This is largely due to

significant variations in heating and cooling demand which differed by as much as 50%

compared to the denser neighbourhood scenario.

The discrepancy could be attributed to both direct shading from the neighbouring buildings on

south facing windows and a reduction in ground reflectance. The significance of this finding is

that rules of thumb for maximum glazing and thermal mass for passive buildings may not apply

in a neighbourhood context. The design of passive solar buildings is a balance between

maximising solar heat gain when required and minimising unwanted solar heat gain so that

thermal comfort can be maintained year round. Hourly simulations that provide indoor space

conditions under passive conditions are useful to assess when and how much passive heating is

provided and to help identify if overheating is a problem. This is especially critical in the month

of October when outside temperatures can be mild and awnings are less effective due to a lower

sun allowing solar rays can penetrate deep into the house.

Building form factors impact such as aspect ratio, height and compactness have direct impacts on

energy use. For Toronto, a more compact aspect ratio of 1.3:1 was found to provide slightly

heating demand than a higher ratio of 1.5:1 during preliminary model development in

RETScreen. The building height and compactness are an important consideration in determining

building spacing and density however, for practical purposes in many low-density single family

neighbourhoods the minimum spacing based on right of way widths which can vary between 17

m and 20 m for residential neighbourhoods could govern the density of a community over

minimum spacing for solar access. While floor heights do not vary considerably among house

designs, the roof slope has a significant impact on the overall building height. The most

appropriate slope depends on if the goal is to maximise heating or to maximise PV production. If

70

the goal is to maximise heating it is desirable to have a steeper slope to maximise solar radiation

in the winter and minimise overheating of the solar collectors in the summer. If the goal is to

maximise PV production then it may be desirable to select a slope that will either maximise

annual PV production with a shallower slope to take advantage of high solar radiation

availability in the summer. On the other hand, a steep slope could provide more balanced PV

production throughout the year and would provide a greater surface area for collectors. A steeper

slope however, results in a taller building which either diminishes the passive heating

performance of neighbouring buildings or decreases the overall density of the development.

These consequences may outweigh the modest additional benefit of a higher roof slope.

When external shading from other buildings and vegetation is introduced into the analysis, the

spatial location of the windows becomes as important. Most basic modeling software and rules

of thumb are based on percentage glazing per floor area or wall area. As a result this prohibits

more basic modeling programs and rules of thumb to accurately account for the impact of

external shading on building energy demand. As demonstrated in the two scenarios, the

townhouse in the denser scenario was less impacted by restricted solar access than the detached

house because a greater proportion of its windows were higher from the ground. Therefore,

higher windows allow for smaller spacing while preserving solar access. The implications of this

for larger residential buildings could be that parking or retail space that would not benefit

significantly from passive solar heat could be located on ground floors while the residential units

are situated higher where they are unshaded from adjacent buildings. Municipal building height

restrictions could also be modified to maximise density and solar access by identifying the ideal

building height for various road types to allow for passive buildings. Cooling loads for a well

designed passive house could have a relatively low sensitivity with density and building spacing

if features such as well designed awnings are used at the building level to control solar radiation

in the cooling season. Figure 5-3 showed for the analysed scenarios that once neighbouring

buildings are introduced into the building energy model there is a region on the graphs where

increasing density does not significantly increase building heating demand until a maximum

density threshold of approximately 26 unit/ha for the detached house and 32 units/ha for the

townhouse is reached where heating demand increases sharply. The location of this threshold

which is a unique signature of each building type and climate is useful in determining the

71

maximum density that would preserve the performance of passive features and aid in locating

buildings in existing neighbourhoods.

Despite density varying by 50% for neighbourhood scenarios, heating and cooling loads

increased only 11% in the detached house and 8% in the townhouse scenarios. This demonstrates

that density can be increased significantly knowing that heating and cooling loads will increase

by a smaller proportion. From a total energy use perspective, the benefits of density due to lower

transportation energy use could offset the benefits of maximizing solar access.

Simulation in a neighbourhood context therefore is useful to assess the sensitivity of such

impacts on building energy use. Municipalities may have development by-laws for maximum

height of buildings, minimum setback distances and road widths. These rules limit density and it

is important to understand what impact they have on building energy demand. Occupancy and

plug loads vary significantly and are difficult to predict however, they have an important

contribution in the overall heating and cooling in passive buildings. A good understanding of

expected plug loads and occupancy loads is very important to understand the impact of passive

solar on heating and cooling requirements.

Occupancy and density defines the metabolism flows through the neighbourhood and roof area

available for PV.

PV was able to produce 2.9 times the electricity demand in the townhouse scenarios and and 4.2

times the electricity demand in the detached house scenarios. The townhouses produced less of

their electricity demand because of their smaller roof area per unit. Electricity demand was not

sensitive with density in the scenarios since density only had a minor impact on auxiliary cooling

loads. Therefore, both townhouse and detached house scenarios produced the same proportion of

their demand through PV. If neighbourhoods were designed specifically for solar access, they

could become net energy producers for buildings with sub-optimal solar access. An ideal

building height to roof area ratio and resulting density likely exists so that a building can meet

exactly all of its electricity needs from PV.

Waste sources were only able to provide 15% of the electricity demand and were insensitive to

density (Figure 6-1). Waste was able to supply 12% to 20% of the demand with higher density

72

townhouse scenarios able to supply more of their demand (Figure 6-2). Unlike heating demand,

electricity demand does not differ significantly between the detached houses and townhouses

explaining why the share of waste electricity production to electricity demand is generally

proportional with increases in density.

Figure 6-1: Potential electricity supply and demand from waste sources

Figure 6-2: Potential heating supply and demand from waste sources

0200400600800

100012001400160018002000

Ener

gy (M

Wh)

Electricity demand

Wastewater

Organic solid waste

Residual solid waste

0

200

400

600

800

1000

1200

1400

1600

1800

MW

h

Heat demand

Organic solid waste

Residual solid waste

73

Specific costs are not included in the scope of this study, however, a menu of potential energy

sources and their orders of magnitude are identified. The most suitable combinations will depend

on government financial incentives available for a particular technology, the relative carbon

intensity of regional electrical and heating supply, and the local infrastructure to support the

technologies such as smart grids, wastewater heat recovery, and energy from waste recovery.

Thermal energy from thermal solar collectors or waste requires a nearby demand to make it

feasible unlike electricity which has year round demand and can be transported greater distances.

The use of thermal energy storage systems is a promising way to store heat energy throughout

the year and draw from it during the heating season. This type of system would enable

communities to increase energy production through combined PV and thermal collectors,

increasing the efficiency of the PV array by reducing their operating temperatures while

increasing the utility of summer solar thermal gains from the heat storage.

This thesis looked only at uniform building types; however, prototypes for other buildings could

be developed to provide load diversity in the community and opportunities to cascade waste heat

from producers such as large office buildings and supermarkets to consumers throughout the

development such as residential buildings in a district system. Ideally, a transient model could be

developed that is able to model and integrate a network of multiple energy sources to model the

potential for district energy systems from both continuous, intermittent sources as well as the

cascading of heat in mixed use neighbourhoods. Potential energy production from the

community metabolism could go further back to account for energy from the agricultural sector

that nourishes the households the food products they consume. An important consideration in

analysing energy options on a community scale is the objective. An objective to minimise

greenhouse gas emissions would require that a priority should be given to low carbon energy

technologies. In such case the carbon intensity of the local energy supply is a significant

consideration. Other objectives could be to minimise energy cost, maximise local energy

production or optimise the use of energy through energy cascading. Transportation can consist of

30-60% of a community’s energy use. It was difficult to incorporate in the generic scenarios

presented however, the impact of density, availability of modes, urban form and location of the

community should be considered in specific planning situations. One example that attempted to

tie the impact of density on solar PV production and transportation energy use is by O’Brien et.

al. (2009). They found that transportation energy use can offset the benefits increased solar

74

availability in low density developments. This demonstrates that holistic look at energy use is

required.

The study of community energy systems is still in its infancy, however, it provides important

insights in understanding the energy impacts of land use planning and uncover important

potential opportunities to optimise energy use and production. In incorporating this type of

analysis in to the planning process it is possible to transform communities and cities toward

sustainability.

75

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