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Real Energy Payback Time and Carbon Footprint of a GCPVS

1 Energy Resources’ Smart Management (ERESMA) Research Group, Department of Electric, Systems and Automatics Eng., University of León, Campus de Vegazana s/n, León, 24071, Spain.
2 Solar andWind Feasibility Technologies (SWIFT) Research Group, Department of Electromecanics Engineering, University of Burgos, Campus de Río Vena s/n, Burgos 09001, Spain.

Special Issues: Solar PV Energy

Grid connected PV systems, or GCPVS, produce clean and renewable energy through the photovoltaic effect in the operation stage of the power plant. However, this is the penultimate stage of the facilities before its dismantlement. Before starting generating electricity with zero CO2 emissions, a negative energy balance exists mainly because of the embodied energy costs of the PV components manufacturing, transport and late dismantlement. First, a review of existing studies about energy life cycle assessment (LCA) and Carbon Footprint of PV systems has been carried out in this paper. Then, a new method to evaluate the Real Energy Payback Time (REPBT), which includes power looses due to PV panels degradation is proposed and differences with traditional Energy Payback Time are analysed. Finally, a typical PV grid connected plant (100 kW nominal power) located in Northern Spain is studied in these sustainability terms. This facility has been firstly completely modelled, including PV modules, inverters, structures and wiring. It has been also considerated the energy involved in the replacement of those components with shorter lifespan. The PV panels degradation has been analysed through the comparison of normalised flash test reports on a significant sample of the installed modules before and 5 years after installation. Results show that real PV degradation affect significantly to the Energy Payback Time of the installation increasing slightly a 4:2% more the EPBT value for the case study. However, along a lifespan of 30 years, the GCPVS under analysis will return only 5:6 times the inverted energy on components manufacturing, transport and installation, rather than the expected 9:1 times with the classical estimation.
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References

1. Perpiñán O, Lorenzo E, Castro M A, et al. (2009) Energy payback time of grid connected PV systems: comparison between tracking and fixed systems. Prog Photovoltaics 17(2): 137–147.

2. Fthenakis V, Alsema E A, de Wild-Scholten M (2005) Life cycle assessment of photovoltaics: perceptions, needs, and challenges, in: Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 1655–1658.

3. Keoleian G A, Lewis G M (1997) Application of life-cycle energy analysis to photovoltaic module design. Prog Photovoltaics 5(4): 287–300.

4. Sherwani A, Usmani J, Varun (2010) Life cycle assessment of solar PV based electricity generation systems: A review. Renew Sust Energ Rev 14(1): 540–544.

5. Tahara K, Kojima T, Inaba A (1997) Estimation of power plants by LCA. Kagaku Kogaku Ronbun 23(1): 93–94.

6. de Wild-Scholten M, Alsema E (2004) Towards cleaner solar PV: Environmental and health impacts of crystalline silicon photovoltaics. Refocus 5(5): 46–49.

7. Fthenakis V, Alsema E (2006) Photovoltaics energy payback times, greenhouse gas emissions and external costs: 2004 – early 2005 status. Prog Photovoltaics 14(3): 275–280.

8. Bayod-Rújula A A, Lorente-Lafuente A M, Cirez-Oto F (2011) Environmental assessment of grid connected photovoltaic plants with 2-axis tracking versus fixed modules systems. Energy 36(5): 3148–3158.

9. Mason J E, Fthenakis V M, Hansen T, et al. (2006) Energy payback and life-cycle CO2 emissions of the BOS in an optimized 3.5 MW PV installation. Prog Photovoltaics 14(2): 179–190.

10. Nawaz I, Tiwari G (2006) Embodied energy analysis of photovoltaic (PV) system based on macroand micro-level. Energ Policy 34(17): 3144–3152.

11. SoDa Team SoDa: HelioClim-3, 2016, Available from: http://www.soda-pro.com/web-services/radiation/helioclim-3-for-free.

12. Europan Commission: PVGIS- PV Potential Estimation Utility, 2016, Available from: http://re.jrc.ec.europa.eu/pvgis/apps4/pvest.php.

13. Hacke P, Smith R, Terwilliger K, et al. (2013) Testing and Analysis for Lifetime Prediction of Crystalline Silicon PV Modules Undergoing Degradation by System Voltage Stress. IEEE J Photovoltaics 3(1): 246–253.

14. Muñoz M A, Alonso-García M C, Vela N, et al. (2011) Early degradation of silicon PV modules and guaranty conditions. Sol Energy 85(9): 2264–2274.

15. Jordan D C, Kurtz S R (2012) Photovoltaic Degradation Rates-An Analytical Review. NREL/JA- 5200-51664 1(1): 1–32.

16. Osterwald C R, Anderberg A, Rummel S, et al. (2002) Degradation analysis of weathered crystalline-silicon PV modules, in: Conference Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conference, 1392–1395.

17. University of Manchester: Carbon calculations over the life cycle of industrial activities, 2016, Available from:http://www.ccalc.org.uk/.

18. Postnote from the Parliamentary Office of Science and Technology: Carbon footprint of electricity generation, 2006, 268:1–4.

19. Díez-Mediavilla M, Alonso-Tristán C, Rodríguez-Amigo M, et al. (2012) Performance analysis of PV plants: Optimization for improving profitability. Energ Convers Manage 54(1): 17–23.

20. Khasawneh Q A, Damra Q A, Salman O H B Determining the Optimum Tilt Angle for Solar Applications in Northern Jordan 9(3): 187–193.

21. Skeiker K Optimum tilt angle and orientation for solar collectors in Syria 50(1): 2439–2448.

22. Government of Spain: Carbon emission factors and primary energy conversion coe cients for the different electrical energy sources in the Building Sector in Spain, 2014, IDAE, 1–32.

23. Alsema E (1998) Energy Requirements and CO2 Mitigation Potential of PV Systems, in: BNL/NREL Workshop PV and the Environment, 1–11.

24. Adelstein J, Sekulic B (2005) Performance and reliability of a 1-kW amorphous silicon photovoltaic roofing system, in: Conference Record of the Thirty-first IEEE Photovoltaic Specialists Conference, 1627–1630.

25. Chamberlin C E, Rocheleau M A, Marshall M W, et al. (2011) Comparison of PV module performance before and after 11 and 20 years of field exposure, in: 2011 37th IEEE Photovoltaic Specialists Conference (PVSC), 101–105.

26. Lorenzo E, Zilles R, Moretón R, et al. (2013) Performance analysis of a 7-kW crystalline silicon generator after 17 years of operation in Madrid. Prog Photovoltaics 22(12): 1273–1279.

27. Espinosa N, García-Valverde R, Urbina A, et al. (2011) A life cycle analysis of polymer solar cell modules prepared using roll-to-roll methods under ambient conditions. Sol Energ Mat Sol C 95(5): 1293–1302.

28. Fthenakis V M, Kim H C (2013) Life cycle assessment of high-concentration photovoltaic systems. Prog Photovoltaics 21(3): 379–388.

29. Hondo H (2005) Life cycle GHG emission analysis of power generation systems: Japanese case. Energy 30(11-12): 2042–2056.

30. Peng J, Lu L, Yang H (2013) Review on life cycle assessment of energy payback and greenhouse gas emission of solar photovoltaic systems. Renew Sust Energ Rev 19: 255–274.    

31. Jiao Y, Salce A, Ben W, et al. (2011) Siemens and siemens-like processes for producing photovoltaics: Energy payback time and lifetime carbon emissions. JOM 63(1): 28–31.

32. Mann S A, de Wild-Scholten M J, Fthenakis V M, et al. (2013) The energy payback time of advanced crystalline silicon PV modules in 2020: A prospective study. Prog Photovoltaics 22(11): 1180–1194.

33. Mohr N J, Meijer A, Huijbregts M a J, et al. (2013) Environmental life cycle assessment of roof-integrated flexible amorphous silicon/nanocrystalline silicon solar cell laminate. Prog Photovoltaics 21(4): 802–815.

34. Yamada K, Komiyama H, Kato K, et al. (1995) Evaluation of photovoltaic energy systems in terms of economics, energy and CO2 emissions. Energ Convers Manage 36(6–9): 819–822.

35. Hammond G, Jones C (2008) Embodied energy and carbon in construction materials. P I Civil Eng Energ 161(2): 87–98.

36. Pacca S, Sivaraman D, Keoleian G A (2007) Parameters affecting the life cycle performance of PV technologies and systems. Energ Policy 35(6): 3316–3326.

37. European Comission: Eurostat database, 2016, Available from: http://ec.europa.eu/ eurostat/data/database.

38. Davis S C, Diegel S W, Boundy R G (2012) Transportation Energy Data Book, volume 1, 31st edition, Oak Laboratory: U.S. Department of Energy.

39. European Environment Agency E U (2016) Explaining road transport emissions, volume 1, 1st edition, Luxembourg: Publications O ce of the European Union.

40. Oficina Catalana del Canvi Climátic E S (2011) Practical Guide for the Carbon Emissions Calculation. Oficina Catalana del Canvi Climátic 1(1): 1–32.

41. Joint Research Centre I E T (Ed.) (2013) Well-to-wheels analysis of future automotive fuels and powertrains in the European context, volume 1, 1st edition, Luxembourg: Publications Office of the European Union.

42. Pucker N, Schappacher W (1994) Installation of new energy systems: Energy balances and installation times; application to a photovoltaic system. Renew Energ 5(1–4): 212–214.

43. Previ A, Iliceto A, Belli G, et al. The 3.3 MW-peak photovoltaic power station at Serre, in: Proceedings of 1994 IEEE 1st World Conference on Photovoltaic Energy Conversion - WCPEC (A Joint Conference of PVSC, PVSEC and PSEC), volume 1, 750–753.

44. Iliceto A, Vigotti R (1998) The largest PV installation in Europe: Perspectives of multimegawatt PV. Renew Energ 15(1): 48–53.

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