Renewable energies in a public forest: viability of possible plant …summerschool-aidi.it/edition-2015/images/Naples2015/... · 2015. 9. 28. · Renewable energies in a public forest:

Renewable energies in a public forest: viability of possible plant technologies

Emanuela Melis *, Francesco Valentino Caredda*, Cristina Pilo**, Pier Francesco Orrù*

*Department of Mechanical Engineering, Chemistry and Materials, University of Cagliari, Via Marengo 2, 09123 - Cagliari - Italy ([email protected], [email protected], [email protected])

** Ente Foreste della Sardegna, Viale Merello 86, 09123 – Cagliari - Italy ([email protected])

Abstract: In this paper, a feasibility study of several technologies for the electrical and thermal energy production, fed with forest residues, is provided. With the aim of identifying the best sustainable energy exploitation of the forest biomass, the work has been developed in the following three main steps: the energy consumption of a buildings complex; a technical and economic evaluation of different configuration plants, along with a sensitivity analysis of some key parameters of the biomass; an environmental assessment via LCA (Life Cycle Assessment).

Keywords: biomass, economic assessment, energy, forest, Life Cycle Assessment

1. Introduction The choice of the plant technologies which are the most viable for the heat and power self-production can be approached by applying different methodologies, and by considering a certain number of perspectives and factors. In particular, when the main interest is focused on determining the feasibility of energy production technologies fed by forest residues (of the forest management), it is necessary to take into account several sub-problems: the amount of biomass annually available for energy purposes, the energy demand of the specific user, the kinds of systems that provide solidity and the market uptake at reasonable prices, with respect to the specific sizes. Last, but not least, factor is the environmental sustainability of the various technological configurations under evaluation for the particular case. The first sub-problem is the quantity of biomass for feeding the plant: in general, a huge number of methods are available for the biomass estimate, but they could lead to different results, depending on the forest management rules, on the characteristics of the territory, as well as on the particular forest species (Orrù et al., 2013). The second sub-problem is related to the energy needs of the buildings and activities to which the future plant is addressed. This part of the feasibility analysis plays a significant role, because the size of the plant highly affects the costs. The technologies feasibility and the cost analyses (third sub-problem) aim at quantifying their economic viability and success. Particularly, the comparison between the costs of different technologies and those of the current configuration (actually used by the consumer) can help us to define the competitiveness of each configuration involved in the analysis. The techno-economic assessment of energy systems has often been performed by simulations and optimisations, using specific software packages (e. g. HOMER) (Zoulias and Lymberopoulos, 2007; Iqbal, 2004), along with the

estimate of the most important economic indicators, such as the Net Present Cost (Dalton et al., 2008). Finally, the last component of the feasibility analysis involves the potential environmental issues caused by the production, use and end of life of the plants. In 2007, the OECD (Organisation for Economic Cooperation and Development) has analysed how the environmental policies do impact on technological change (Vollebergh, 2007): by a papers review, it has concluded that the environmental policy has a general impact on the direction of the technological change and innovation. In fact, also new studies confirm this relationship between the environmental policy and empirical research in the field of the technological R&D (Johnstone and Haš�i�, 2013; Nemet, 2013; Nesta et al., 2014). With particular reference to the rising global interest on climate change, the related policy has been targeted on the green technologies and the low-carbon economy (Dowling, 2013). So, a lot of studies have been developed in this field (e. g. Mishra et al., 2014; Sapkota et al., 2014) and the technologies are dealing with the emissions reduction per output energy unit, by achieving also optimal efficiencies and costs. Nowadays, it represents a great challenge for the future. The present work has taken into account all the above discussed sub-problems (with the exception of the first one, developed in a previous work (Orrù et al., 2013)), by analysing the economic viability of possible plant technologies, for meeting the thermal and electrical demands of a buildings complex within a public forest in the South of Italy. The major aim of those evaluations has been the feasibility of the forest biomass residues use for energy production, by comparing the current situation to a number of technological scenarios. Firstly, an energy diagnosis of a buildings complex located in the study area has been performed. Then, a techno-economic evaluation of different plant technologies and sizes has been conducted for the best technological alternative for the case under consideration. Finally, the

XX Summer School "Francesco Turco" - Industrial Systems Engineering

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environmental impacts of three selected plant configurations been carried out in a life cycle perspective. 2. Approach 2.1 Energy demand of the buildings The object of the analysis is a buildings complex located into the boundaries of the Monte Olia forest. The complex is composed by six buildings: two twin buildings (424 m2 each) (Figure 1), used for offices and lodgings; one building (Figure 2) used by the site keeper (36 m2); one building for workshop and warehouse (145 m2); one building for garage and carpentry (304 m2) and one building used as a workers shelter (130 m2).

Figure 1: the two main buildings of the Monte Olia

complex

The first step of the work has involved an energetic diagnosis of the buildings, aimed at obtaining the information for the energy consumption estimate. Those evaluations have been performed by distinguishing the intended usages of the spaces. Furthermore, the most significant thermo-physical characteristics have been calculated for the subsequent implementation of numerical models, to be used for dynamic simulations. Particularly, they concern: the geometric data of each building (derived by design drawings and campaign determinations); the intended usages of the spaces; the transmittance data, by the means of a heat flow meter, in accordance to the ISO 9869-1:2014 . Then, the hourly thermal loads (distinguished in heating and cooling) of each building have been estimated by performing dynamic simulations, carried out by using the TRNSYS-TRNBUILD software (16 version). The warehouse and the carpentry have been discarded and the simulations have been conducted on the remaining structures. The buildings models have been implemented into the TRNBUILD application of TRNSYS, by considering the geometric and structural data (audit results). The outdoor climate data (Table 1), to be used as input for the numerical model, have been assessed by means of

the Meteonorm software, by taking as reference the geographical position of the site and the average altitude.

Figure 2: building used by the site keeper

Table 1. Average Monthly Climatic Data of the Monte Olia site

Average Monthly Climatic Data

Temperature Humidity Radiation January 9.1 78.1 2.10

February 8.5 76.6 2.88 March 10.3 76.8 4.19 April 11.9 77.3 5.34 May 16.2 75.0 6.19 June 20.0 72.3 7.18 July 22.1 71.9 6.90

August 23.0 72.5 6.14 September 19.4 76.7 4.94 October 17.2 77.9 3.38

November 12.6 77.8 2.28 December 9.7 76.7 1.87

Annual Average 15.1 75.8 4.46

°C % kWh·m-2·d-1

The outdoor temperature and humidity, as well as the operation time of the systems, have been estimated by applying the Italian regulations, on the basis of the actual use (D.P.R. n. 412, 1993). An outdoor temperature of 20 °C for the heating period has been considered, whereas a temperature of 26 °C for the cooling period has been fixed. The relative humidity falls into the range 40% - 60%. According to the national regulations, the heating period goes from November 1 to April 15, while the use of the thermal generators has been fixed to 11 hours per day, from 06 a.m. to 5 p.m. The domestic hot water (DHW) consumption has been estimated in accordance to the UNI/TS 11300-2:2008, by involving the floor surfaces, the occupation and the specific activities carried out in each space. The interviews with the users, mostly focused on their conventional activities, have led us to assess the average daily hourly distribution of the loads, since it has not been possible to obtain the hourly values. Campaign measurements and consumption bills have been used for the estimation of the electrical energy loads. The daily DHW distribution has been considered for the hourly thermal loads assessment.


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1.2 Techno-Economic feasibility analysis The techno-economic assessment has been performed with the aim of identifying the most viable plant solution for the self-production of energy. This step of the study has aimed at lessening the energy supply cost. Different technologies for the heat and power production have been considered, with the below indicated hypotheses: • the replacement of the current thermal energy

production system (fuel oil boiler) with a forest biomass boiler;

• the installation of a combined heat and power (CHP) system, consisting in a Stirling cycle engine, coupled (by means of a heat exchanger) to a forest biomass boiler;

• the use of photovoltaic systems (PV); • the absorption chillers installation, instead of

electrical heat pumps. The assessment has been performed using the HOMER software (www.homerenergy.com). Each alternative has been examined and, then, combined with the others. The results have consisted in different energy systems. Those ones represent more complex integrated systems. The sizes and technologies commingling has led us to finally obtain 144 manifold configurations to be analysed. The costs of the involved configurations are shown in Table 2 (see Appendix). The main technical specifications for the PV and the CHP systems are summarised in the Tables 3a-3b.

Table 3a. Technical specifications of the PV system

Photovoltaic System Coefficient of Power

(temperature) -0.30 %·°C-1

Nominal Operating Cell Temperature (NOCT) 44 °C

Efficiency (test conditions) 19 % Lifetime 20 years

Tilt Angle 40 ° Azimuth 0 °

For the economic analysis, a time window of 20 years and a 5% of interest rate have been set. The evaluation of the system configurations viability has been done by taking into account, as reference indicator, the Net Present Cost (NPC). Subsequently, also the following economic indicators have been applied as well: the Net Present Value (NPV), the Payback Time (PBT) and the Internal Rate of Return (IRR). For the costs evaluation of the current scenario (diesel boiler with the power purchase from the grid), we have used the below indicated values and costs:

• Diesel fuel price (Lower Heating Value of 43.2 MJ·kg-1): 1.4 €·L;

• Electricity price: 30·10-2 €·kWh-1. This value includes all the costs and duties.

Table 3b. Technical specifications of the CHP system CHP Stirling Engine

Nominal Electrical Efficiency 13.2 % Nominal Thermal Efficiency 69.5 %

Lifetime 20000 hours 1.3 Sensitivity analysis The techno-economic analysis has been developed by considering a forest biomass LHV of 16.4 MJ·kg-1 and a wood cost of 0 €·t-1. The latter has been chosen because the Monte Olia forest has multiple purposes, so the biomass removal comes from the forestry interventions. They are in line with the principles of the sustainable silviculture (Larsen, 1995), the systemic silviculture (Ciancio and Nocentini, 1996-2011; Ciancio et al., 2003), the minimum forest stock (Nocentini et al., 2011) and the Safe Minimum Standard (Toman, 1992). It has to be taken into account the variability of the two above mentioned parameters, thus two sensitivity analyses have been performed, aimed at verifying the relationship between this variation and the possible changes in the best plant configuration selection. Moreover, the sensitivity analysis has involved also the results of the economic analysis, especially with reference to the NPC. The first part of the sensitivity analysis has examined the variation of the previously described economic indicators, by changing the biomass LHV inside the range 8 – 20 MJ·kg-1. The latter has been conducted by applying a wood cost between 0 and 15 €·t-1, being the maximum value the actual price applied by Ente Foreste della Sardegna for the fresh pine logs in the Monte Olia forest. 1.4 Environmental impacts of the selected plant scenarios The most important objective of this step of the work is to evaluate if the most sustainable plant configuration for the case under study is also the most economically viable. The environmental analysis has been performed by considering the main physical and chemical characteristics of the forest species within the study area, as well as the results of the techno-economic analysis. The former are 12 samples of Mediterranean conifers (Pinus pinea, Pinus pinaster and Pinus halepensis). For each species, two trees have been harvested and, for each of them, two samples have been collected: one of log with bark and biggest branches, one of small branches and needles. They have been chipped and, then, analysed (proximate and ultimate analyses, heating value determination, humidity). The results on wet basis (hereinafter “as received”) have been averaged, in order to obtain a single value for each parameter and, thus, to define the average characteristics of the Monte Olia forest biomass. The environmental assessment has been based on the Life Cycle Assessment (LCA) approach and it has involved three plant scenarios (see sect. 3.2). We have carried out a “gate to grave” LCA, by the means of the GEMIS software and databases and by taking into account the production, use and end of life of the plants. The production and transportation of the fuels have been excluded.


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The annual thermal and electrical demands have been used as reference for the inventory data collection and the resulting life cycle impact assessment. Some processes into the GEMIS software have been modified, because of the specific plant sizes, operation times, efficiencies and so on. For the biomass boiler, it has also been necessary to modify the kind of biomass, by introducing a new product: the Monte Olia biomass and its main characteristics (C, H, N, O, S, ash content, humidity, LHV). Then, the Life Cycle Impact Assessment (LCIA) has been performed using the OpenLCA software. The ReCiPe method has been chosen for the analysis. Thus, the LCIA has been conducted and the results have subsequently been compared. The emissions of the green house gases (GHG), summarised into the Climate Change category (which converts the above mentioned emissions into kg CO2-equivalent emissions), define the Carbon Footprint of each scenario. A second environmental analysis has been carried out, by calculating the embodied solar energy (emergy). Emergy is defined as the solar energy used directly and indirectly to generate a service or product (Cao and Feng, 2007). Its unit is the solar emJoule (seJ) and it is based on the transformity concept: it describes the solar energy for the production of a unit of product. The transformity is the amount of seJ per J or kg of product (seJ/J, seJ/kg). The energy effectiveness of a system depends on this parameter: lower values of solar transformity are related to a lower emergy for the production of a specific quantity of product (Sha et al., 2013), thus the energy effectiveness becomes higher. For the calculations, all the input matter and energy flows have been considered. As a reference database of the transformities values, we have used the emergy database developed by the International Society for the Advancement of Emergy Research. When it has not been possible to use those data, other sources have been considered (Roudebush, 1998). The inventory flows, related to 1 kWh of energy produced by each component of the three scenarios, have been multiplied with the relative transformities, to obtain the seJ values per unit of product. Subsequently, those values have been multiplied with the annual amount of kWh produced by each component of each scenario. By summing the seJ of all the components of each scenario, we have, then, obtained the results for the three scenarios. The comparison between these values has led us to determine the effectiveness of the three selected energy systems. By the two environmental evaluations (LCIA, embodied solar energy), the selection of the most sustainable plant configuration for the specific case has been achieved. 3. Results and Discussion 3.1 Energy demand assessment The annual energy consumption of the Monte Olia buildings complex is about 33.9 MWhel and about 64.5 MWhth, corresponding to 6554 l of diesel fuel per year. The monthly consumption is shown in the Tables 4 and 5.

The electricity is purchased from the grid. The allocation of the annual electricity demand, with respect to the three following consumption items, is indicated below:

• Lighting: 7 MWh (20.7%) • Electromotive force: 21.3 MWh (63%) • Air conditioning: 5.5 MWh (16.2%).

Table 4. Energy purchased by the Monte Olia buildings

complex

Total Energy Demand [kWh]

Thermal (Fuel) Electricity (Grid)

January 12910 2542 February 11746 2468 March 9840 2506 April 3209 2488 May 1069 2380 June 1034 2929 July 1069 3641

August 1069 4186 September 1034 2778 October 1069 2867

November 7837 2542 December 12609 2542 Total Year 64495 33872

By the integration of the hourly values of the dynamic simulations, 41.6 MWh for heating and 13.7 MWh for cooling have been calculated as annual thermal loads. About 830 litres of daily consumed DHW have been estimated, which mean to an annual energy consumption of about 10 MWh.

Table 5. Thermal Energy Demand of the Monte Olia

buildings

Thermal Energy [kWh]

Heating DHW Cooling January 9478 856 0

February 8630 773 0 March 7021 856 0 April 1741 828 80 May 0 856 550 June 0 828 1953 July 0 856 3072

August 0 856 5064 September 0 828 1487 October 0 856 910

November 5446 828 0 December 9238 856 0

Total 41554 10074 13747 3.2 Techno-Economic feasibility analysis The techno-economic feasibility assessment, which has involved the earlier described 144 plant configuration scenarios, has led us to select three scenarios (Table 6), hereinafter indicated as A, B and C. The A scenario is the current configuration (oil-fired boiler for the thermal energy production and the power purchase from the grid). The NPC for the A scenario is of 263.4 k€, which leads to 21.136 k€ of annual cost. The B scenario has emerged as the most viable plant configuration among those considered in the present


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work: it consists in a 80 kWth forest biomass boiler for the thermal energy production, with a 20 kWel PV system and a limited purchase of the electricity from the grid. Finally, the C scenario is the most economically affordable between the involved CHP systems. It is represented by a 5 kWel Stirling CHP system and a oil-fired boiler as an auxiliary system. The B scenario allows self-producing the thermal energy demand of the service buildings for heating and DHW. Thanks to 40 kWth heat pumps, it may produce the necessary cooling. By the techno-economic analysis, it has come to state that the absorption systems for summer cooling are not economically viable. The power energy production is realised by the means of a photovoltaic system, which could self-produce more than 90% of the electricity demand. The remaining part will be purchased from the electrical grid. The energy consumptions estimated for the B scenario are: 14 tons per year of forest biomass and about 2462 kWh per year of purchased electricity. The renewable energy potentially produced by this system is 97% circa. By considering the investment, the NPV is about 59 k€, with an initial investment of 57 k€; in addition, the estimated payback time is of 7.4 years. The Figure 3 shows the costs distribution for the A and B scenarios. The small size of the Stirling engine, along with the low energy loads involved in the C scenario, have led us to assert that this CHP system is technically feasible, but still not economically viable. Indeed, the high costs (NPC of 248.652 k€) and the scanty technical performance, related to low self-production of energy are the main reasons for rejecting this specific plant configuration.

Table 6. The technical and economic feasibility analysis results

Results Scenarios

A B C

Self-production: Electrical Energy 0% 92.7% 17.9%

Self-production: Thermal Energy 0% 100% 57.0%

Renewable Energy Source Production 0% 97.3% 42.6%

Biomass Consumption (t·yr-1) 0 14.2 10.4

Diesel Fuel Consumption (l·yr-1) 6554 0 2820

Electricity Grid Purchase (kWh·yr-1) 33872 2462 27810

NPC (€·yr-1) 263400 155841 248652

NPV (€) /// 59035 14748

PBT (yr) /// 7.4 10.2

IRR (%) /// 14.95 9.52

Figure 3: costs distribution (%) for the A and B scenarios

3.3 Sensitivity analysis The sensitivity analysis, carried out on the LHV of the Monte Olia forest biomass, has allowed us to verify that the results are not dependent on the kind of technological scenario (biomass cost set to 0 €·t-1). Thus, the LHV variation only affects the quantity of biomass used by the plant, without an impact on the economic viewpoint. Further evaluations involving those two parameters could allow obtaining different results, with respect to those arising from the present study. With the second step of the sensitivity analysis, the biomass cost has been changed, because of the strong influence of this factor on the selection of the most viable plant configuration. For the lower limit of the biomass cost range (0 €·t-1), the most economically suitable plant is the B scenario, but the biomass cost rising leads to better economical performances by considering higher sizes for the CHP systems (5-10 kWel), coupled with PV systems. The management costs of the plants become higher, when the wood cost increases: specifically, for the lower limit of the biomass cost, the NPC is about 500-600 k€; for 10 €·t-

1, we have obtained 900 k€ of NPC and finally, for a wood cost of 15 €·t-1, the NPV is about 1200 - 1300 k€. 3.4 Environmental Impacts of the Selected Plant Scenarios

The Life Cycle Inventories (LCI) of the three above described scenarios have been compared, by considering only the emissions into air and into water and the waste production/end of life. The emerging best scenario is B, because of the lowest values for most of the emissions/wastes. This is true, moreover for the GHG. The Carbon Footprint, which involves the most significant GHG emissions derived from the LCI (CO2, CH4, NOx), is represented in the below graphic (Figure 4). Subsequently, the LCIA has been conducted and the environmental impacts obtained for each scenario are summarised in the Table 7 (see Appendix).


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Specifically for the impact categories of: Climate Change, Freshwater Ecotoxicity Freshwater Eutrophication, Human Toxicity, Marine Eutrophication, Particulate Matter Formation, Photochemical Oxidant Formation and Terrestrial Acidification, the B scenario is the most sustainable. On the contrary, the A scenario is the worst. The embodied solar energies estimated for the three scenarios are reported in the Table 8.

Figure 4: annual Carbon Footprints of the A, B, C scenarios

Table 8: the embodied solar energies of the A, B, C

scenarios

A scenario B scenario C scenario

seJ per year 3.24E+16 2.63E+15 2.07E+16 4. Conclusion In this paper, aimed at identifying the most suitable energy production technology for the Monte Olia forest biomass residues exploitation, two different approaches have been applied. The former has consisted in a techno-economic assessment, the latter has been based on the Life Cycle Assessment methodology. Firstly, the energy consumption of the buildings complex has been quantified. It has allowed us to obtain also the necessary data for the implementation of dynamic models, which describe the thermo-physical behaviour of the buildings. By using them, implemented in the TRNSYS software, we have obtained the hourly thermal loads (heating and cooling). The last ones have led us to evaluate different technical solutions: forest biomass boiler, CHP systems by using small Stirling cycle engines, trigeneration, PV systems. By the dynamic simulations, realised by means of the HOMER software, the most economically viable plant configuration has been selected: it consists in a 80 kWth forest biomass boiler with a 20 kWel PV system, and a limited power purchase from the electrical grid. For a more detailed analysis, three different scenarios have been identified: the current configuration (oil-fired boiler, power purchased from the grid), the most economically viable scenario, and a CHP system (biomass boiler coupled to a 5 kWel Stirling engine). The most suitable scenario has an initial investment of 57 k€. The related NPV is of 59 k€ and the IRR is of 7.4 years. By performing a sensitivity analysis on the biomass LHV and the biomass cost, we have analysed the effects of

those ones on the best plant configuration and on the annual maintenance costs. The environmental assessment, conducted on the three selected plant scenarios, has consisted in Life Cycle Assessment and in the embodied solar energy estimate. LCA, performed by the means of the GEMIS database and software and the OpenLCA software, has taken into account the production, use and end of life of the three systems. The environmental assessment has considered the results of the energy demand assessment, the biomass samples characterisation and the techno-economic analysis. This environmental evaluation has confirmed the most economically viable plant configuration as the most suitable for the case under consideration. By estimating the embodied solar energy for the annual production of the heat and power needs of the Monte Olia buildings complex, it has come to assert that the lower value is related to the most economically viable scenario. So, we have found the convergence of the results for the two environmental evaluations and the techno-economic analysis. Acknowledgments The research has been funded by Ente Foreste della Sardegna through a three-year agreement. The research has been carried out within the “Master And Back” Program of the Sardinia Autonomous Region. References

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D.P.R. n. 412 (1993). Regulations for the design, installation, operation and maintenance of heating systems in buildings in order to control the consumption of energy, in fulfilment of art. 4, paragraph 4, of the Law 9 January 1991 n. 10.

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Appendix

Table 2. Costs of the considered systems configurations

Biomass Boiler [Efficiency=90%] Size (kWth) Plant Cost (€) Replacement Cost (€) Management Costs (€·yr-1)

80 25000 20000 1000 Cooling System No. 1: Absorption systems [Energy Efficiency Ratio =0.6]

Size (kWcool) Plant Cost (€) Management Costs (€·yr-1) 8 15300 750 16 21900 1100 24 27000 1400 32 32300 1550 40 35100 1800

Cooling System No. 2: Heat pump [Energy Efficiency Ratio=2.5] Size (kWcool) Plant Cost (€) Management Costs (€·yr-1)

8 3800 200 16 6600 300 24 9100 450 32 11400 600 40 13700 700

Stirling Engine CHP system Size (kWel) Plant Cost (€) Replacement Cost (€) Management Costs (€·h-1)

2 16000 12000 1.5 5 35000 25000 1.8 10 55000 45000 2.0 20 80000 65000 2.5 30 105000 80000 3.0

Photovoltaic System Size (kWel) Plant Cost (€) Replacement Cost (€) Management Costs (€·yr-1)

2 4600 4000 300 5 10000 9000 500 10 18000 16000 1000 20 32000 28000 1500 30 42000 37000 2000

Table 7. Environmental Categories and the respective results for the three plant configuration scenarios

Impact Category Unit A scenario B scenario C scenario

climate change - GWP100 kg CO2-Eq 3.79E+04 1.65E+03 2.73E+04

freshwater ecotoxicity - FETPinf kg 1,4-DCB-Eq 2.92E-03 5.97E-04 2.18E-03

freshwater eutrophication - FEP kg P-Eq 2.50E-05 3.09E-06 1.95E-05

human toxicity - HTPinf kg 1,4-DCB-Eq 9.65E+00 5.35E-01 6.20E-01

marine ecotoxicity - METPinf kg 1,4-DCB-Eq 2.37E-02 4.27E-03 3.57E-03

marine eutrophication - MEP kg N-Eq 1.08E+01 1.28E+00 1.17E+01

particulate matter formation - PMFP kg PM10-Eq 1.21E+01 1.34E+00 1.32E+01

photochemical oxidant formation - POFP kg NMVOC 3.39E+01 6.40E+00 4.06E+01

terrestrial acidification - TAP100 kg SO2-Eq 4.59E+01 4.95E+00 5.00E+01

terrestrial ecotoxicity - TETPinf kg 1,4-DCB-Eq 1.90E-03 2.69E-04 1.89E-04


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