By: Ramy Essam. Under Supervision of: Prof. Dr. Mohammed Fawzy Elrefaie Prof. Dr. Dirk Dahlhaus

Transcription

1 By: Ramy Essam Under Supervision of: Prof. Dr. Mohammed Fawzy Elrefaie Prof. Dr. Dirk Dahlhaus 1

2 Outline 1. Introduction & Objective 2. Methodology & Procedure 3. Modeling 4. Simulation & Results 5. Conclusion 6. Future Recommendations 7. Summary 8. Questions & Answers 2

3 1. Introduction & Objective Definition: Agro-photovoltaic (APV) is the concept of combining power generated from PV and to enhance Agriculture productivity simultaneously Aim of work: The PV integration on farm land concept is used to increase land productivity and economic profitability with minimal negative interactions and positive optimal interactions Source: Objective of the study: Evaluation of technical and economical feasibility under Egyptian climate conditions 3

4 2. Methodology & Procedure Identify the Problem & Search for Solutions 1. Define Technical Model Variables 2. Classification of Plants Run the Simulation Interpretation of results & Conclusion History of APV applications Literature review Lessons learned: Fraunhofer ISE/In-house research Literature experimental shading studies Radiance Software 4

5 2. Methodology & Procedure 2.1. History of APV Sources: 1- Fraunhofer ISE; 2- M. Guggenmos; University of Montpellier Prof. A. Goetzberger (early 80s) published preliminary results of research. Putting it into practice: Bavaria (since 2010): Manfred Guggenmos: practical experiments for vegetables under PV. Northern Italy (2011): three APV-prototypes have been installed, but no scientific support to date. South of France (2009): University of Montpellier installed APV testing facility. 5

6 3. Modeling 3.1. Modeling- Agriculture Aspects Source: Plant growth conditions are a subject to change with APV implementation Evaluation according to ecological indicator values of plants. Ecological indicators Interpretation against field of reference 6

7 Biomass yield [%] 3. Modeling 3.1. Modeling- Agriculture Aspects PLUS ZERO MINUS Photosynthetic Active Radiation (PAR) [%] Figure (1): Biomass Yield as a Function of Relative Light Availability (PAR) Plants react differently on shading Response to shading of crops in arid regions 7

8 3. Modeling 3.1. Modeling- Agriculture Aspects Figure (2): Classification of Egypt s most relevant economic plants in agriculture PLUS category: Shading tolerant, crops are benefited from shade ZERO category: No significant effect on yield MINUS category: Shading sensitive, crops are badly influenced by shade 8

9 3. Modeling 3.1. Modeling- Technical Aspects 1 = PV module 2 = foundation of intermediate supports 3 = foundation at the edge of the field α = surface azimuth angle b = module width d = row spacing d = distance between supports L= modules length h = clear height underneath the panels Figure (3): APV System Technology 9

10 4. Simulation & Results 4.1. Technical Variables Inclination Angle (15, 25 ) Height of Installation (2m, 4m & 6m) Orientation Angle (0, 45 ) Row Spacing Distance ( m) Figure (5): Simulation of Irradiance on Ground Figure (4): Side View of an APV Module System Structure 10

11 4. Simulation & Results 4.2. Technical Results Global Horizontal Irradiation vs Height Increasing height shows higher uniformity of solar irradiation distribution on ground. Installation height of 4 m is to be considered for the upcoming calculations. Figure (6): Global Horizontal Irradiation underneath Different Installation Heights. 11

12 4. Simulation & Results 4.2. Technical Results Global Horizontal Irradiation vs Orientation angle Figure (7): Global Horizontal Irradiation underneath Different Orientation of Arrays. Optimal module orientation towards South results in heterogeneous distribution of radiation on ground level. Orientation towards 45 South-west provides homogeneously distributed Irradiation. Conclusion: Homogeneity of radiation is very important for crop cultivation ( simultaneous ripening, etc.) therefore, modules should have to be installed: High Not towards South 12

13 PVE [%] 4. Simulation & Results 4.2. Technical Results Photovoltaic Electric Yield Summer-South Winter-South Summer-Southwest Winter-Southwest Row Spacing Distance [m] Figure (8): Photovoltaic Electric Yield G t d;α D (degree of surface coverage) PVE rel d; α = 100 G t 1.5;0 D (OPTIMAL degree of surface coverage) Orientation of array in an APV system towards 45 south-west. Electricity yield decreases by less than 5 % due to this suboptimal orientation. 13

14 PAR [%] 4. Simulation & Results 4.2. Technical Results Photosynthetic Active Radiation Summer-South Winter-South Summer-Southwest Winter-Southwest Row Spacing Distance [m] Figure (9): Photosynthetically Active Radiation on Ground between modules PAR rel d = G hor G hor d;α;under module unshaded area 100 Photosynthetic active radiation in winter South-west oriented is higher than in South oriented. 14

15 BME [%] BME [%] 4. Simulation & Results 4.2. Technical Results Biomass Yield 140 Standard Orientation: South 140 Standard Orientation: 45 South-west PLUS-Summer PLUS-Winter ZERO-Summer ZERO-Winter MINUS-Summer MINUS-Winter Row Spacing Distance [m] PLUS-Summer PLUS-Winter ZERO-Summer ZERO-Winter MINUS-Summer MINUS-Winter Row Spacing Distance [m] Figure (10): Biomass Yield of APV south and 45 -Southwest oriented modules 45 South-west facing system and 25 inclination angle is a good regime to measure the effect of changing row spacing distance on the three categorized crops. Slight differences, but only for winter crops. 15

16 LER 4. Simulation & Results 4.2. Technical Results Land Equivalent Ratio 2 1,8 1,6 1,4 1,2 1 0,8 PLUS-Summer PLUS-Winter ZERO-Summer ZERO-Winter Row Spacing Distance [m] Figure (11): Land Equivalent Ratio LER = BME APV BME mono + PVE APV PVE mono It is a quantitative approach for determining productivity of APV, it measures the total output per unit area. LER for summer crops of PLUS category increased by 80 % productivity at optimum row spacing of 2.9 m. LER for the other two categories are in the range of 30 to 60 % higher in productivity compared to monocultivation. 16

17 4. Simulation & Results 4.3. Technical & Economical Input Parameters Technology Parameters Unit PV off APV off APV on Operating Lifetime [a] Surface Area [ha] Investment Cost * [ /kwp] 1,210 1,700 1,700 Module Width [m] Row Spacing Modules [m] Rated Capacity of Module [W/m2] Installed Capacity ** [kwp] Power Generation Yield *** [kwh/m 2.a] 1, , ,700 1 PV System Power Generation [kwh/a] 1,210, , ,205 Financial Parameters Debt Percentage [%] Equity Percentage [%] Loan Repayment Time 5 [a] Weighted Average Cost of Capital (WACC) [%] Cost of Equity [%] Beta Factor [-] Annual Current Output Reduction [%] Price of Electricity [ /kwh] Annual Operating Expenses [%] (as a percentage of investment) Leased Land [ /a] Agricultural Income [ /a] Table (1): Input Technical and Financial Parameters for Economic Feasibility 17

18 4. Simulation & Results 4.4. Economical Results Results Unit PV off APV off APV on Lifetime [a] Total Investment Cost 10 [ ] 818, , ,000 Total Power Generation 11 [kwh] 29,557,833 17,018,146 17,018,146 Revenue on Sale of [ ] 4,138,096 2,382,540 1,174,252 Electricity Maintenance Cost 12 [ ] 409, , ,500 Net Income Electricity [ ] 2,910,249 1,337, ,752 Net Income Agriculture [ ] 0 32,836 32,836 Total Net Revenue [ ] 2,910,249 1,369, ,588 Present Value (PV) [ ] 1,716, , ,961 Weighted Average Cost of [%] Capital (WACC) Net Present Value (NPV) [ ] 898, , ,038 Internal Rate of Return (IRR) Electricity Generation Costs (LCOE) [%] [ /kwh] Table (2): Results of the Investment Analysis of an APV System in comparison with a Conventional PV System 18

19 4. Simulation & Results 4.5. Sensitivity Analysis-Investment Cost NPV [*1000 /ha] IRR [%] NPV IRR Investment cost [ /kwp] Figure (12): The influence of Investment cost on the NPV and IRR for APV off-grid scenario. 19

20 4. Simulation & Results 4.6. Sensitivity Analysis-Electricity Cost NPV [*1000 /ha] IRR [%] ,02 0,04 0,06 0,08 0,1 0,12 0,14 0, NPV IRR -400 Electricity cost [ /kwh] 0 Figure (13): The influence of Electricity cost on the NPV and IRR for APV on-grid scenario. 20

21 5. Conclusion APV off-grid Technology is Technically and Economically fesible. APV off-grid scenario can compete with PV scenario by decreasing the investment cost and for APV ongrid by increasing the price of electricity (Feed-in Tariff). In the off-grid scenario, reducing the investment cost due to relying on local material of construction. Result in APV-off grid technology could still compete with a PV system. Coexisting of PV and plant cultivation is theoretically feasible in Egypt and practically proven elsewhere (e.g. France and Italy) (In Egypt: only if economic framework will be established) 21

22 6. Future Recommendations 6.1. APV Potential-Case Study in Minya P = Surface area P APV,ha APV-Potential in Egypt equals GWp. APV-Potential in Minya equals MWp. Potential Restriction P APV,ha Surface Area P [kwp/ha] [ha] [MWp] Theoretical Agriculture Land Technical Plants of Categories PLUS and ZERO Technical Assumption: Sustainability of 5-10 % of the area Table (3): Assessment of Theoretical and Technical Potential of APV in Minya Sekem and Fraunhofer ISE intend to kick-off a pilot project in Egypt 22

23 6. Future Recommendations 6.2. Recommendation for Action Recommended to Calculate: Amount of irrigation water savings. GHG emissions due to the replacement of APV-electricity to diesel generators in offgrid regions. Source: Green Valley Farm, SEKEM. 23

24 6. Future Recommendations 6.3. Uncertainties and Future Work Some results of the present study based only on theoretical assumptions, their validation is still pending. The three dominant uncertainties that should be examined are: Data basis for assessing the shade tolerance of crops Yield models of the three plant categories Boundary conditions of the economic analysis Source: Green Valley Farm, SEKEM 24

25 7. Summary Finally, the use of APV still appears to be a significant and purposeful approach to enhance the productivity of the same land area between agriculture and energy sector. Source: 25

26 8. Questions & Answers Thank you very much for your attention 26