Impact of Climate Change on the Performance of Household-Scale Photovoltaic Systems

Nándor Bozsik, András Szeberényi, Norbert Bozsik


The objective of this article was to investigate the impacts of climate change on photovoltaic systems among renewable energies by the end of the 21st century. One hypothesis posited that due to decreased cloud cover as a result of changing climate, the geographical region under examination would receive more solar irradiation—usable by photovoltaic panels—which would in turn increase the annual electrical energy production of these systems. Another hypothesis suggested that the average temperature increase, associated with changing climate conditions, would detrimentally affect the efficiency of electricity production in photovoltaic systems. The study was based on the simulation of a household-scale photovoltaic model. This simulation calculated the system's performance on an hourly basis depending on inputs and summed these to produce an annual value. Input values were derived from climate scenario databases. These variables included global horizontal irradiance, direct horizontal irradiance, temperature, and wind speed. The output was the aforementioned quantity of annual electrical energy production. An analysis occurred between the annual average global horizontal irradiance and the annual average air temperature in relation to the quantities of annual electrical energy production. Pearson and partial correlation examinations among the variables demonstrated that unfavorable scenarios resulted in reduced efficiency of photovoltaic electrical energy production, primarily due to rising temperatures. Among other contributions, this article can support research into the active cooling of photovoltaic systems and the examination of their viability to mitigate efficiency losses caused by current and future temperature increases.


Doi: 10.28991/HIJ-2024-05-01-01

Full Text: PDF


Solar Panel; Warming; Efficiency; Climate Change; RCP Scenario.


Simioni, T., & Schaeffer, R. (2019). Georeferenced operating-efficiency solar potential maps with local weather conditions – An application to Brazil. Solar Energy, 184, 345–355. doi:10.1016/j.solener.2019.04.006.

Singh, P., & Ravindra, N. M. (2012). Temperature dependence of solar cell performance - An analysis. Solar Energy Materials and Solar Cells, 101, 36–45. doi:10.1016/j.solmat.2012.02.019.

Schuster, C. S. (2020). The quest for the optimum angular-tilt of terrestrial solar panels or their angle-resolved annual insolation. Renewable Energy, 152, 1186–1191. doi:10.1016/j.renene.2020.01.076.

Campos, J., Csontos, C., & Munkácsy, B. (2023). Electricity scenarios for Hungary: Possible role of wind and solar resources in the energy transition. Energy, 278. doi:10.1016/

Atsu, D., Seres, I., & Farkas, I. (2021). The state of solar PV and performance analysis of different PV technologies grid-connected installations in Hungary. Renewable and Sustainable Energy Reviews, 141. doi:10.1016/j.rser.2021.110808.

Madaleno, M., Ahmed, Z., Doğan, B., Javeed, S., & Vasa, L. (2023). The aptness of import-led growth hypothesis for sustainable development in South Asia: Do energy utilization and natural resources matter? Resources Policy, 86. doi:10.1016/j.resourpol.2023.104262.

Baglivo, C., Congedo, P. M., & Mazzeo, D. (2023). Scenarios for urban resilience—perspective on climate change resilience at the end of the 21st century of a photovoltaic-powered mixed-use energy community in two European capitals. Adapting the Built Environment for Climate Change: Design Principles for Climate Emergencies, Woodhead Publishing, 37–52. doi:10.1016/B978-0-323-95336-8.00012-3.

Copiello, S., & Grillenzoni, C. (2017). Solar Photovoltaic Energy and Its Spatial Dependence. Energy Procedia, 141, 86–90. doi:10.1016/j.egypro.2017.11.017.

Oka, K., Mizutani, W., & Ashina, S. (2020). Climate change impacts on potential solar energy production: A study case in Fukushima, Japan. Renewable Energy, 153, 249–260. doi:10.1016/j.renene.2020.01.126.

Abdulai, D., Gyamfi, S., Diawuo, F. A., & Acheampong, P. (2023). Data analytics for prediction of solar PV power generation and system performance: A real case of Bui Solar Generating Station, Ghana. Scientific African, 21. doi:10.1016/j.sciaf.2023.e01894.

Ghimire, S., Deo, R. C., Casillas-Pérez, D., & Salcedo-Sanz, S. (2022). Boosting solar radiation predictions with global climate models, observational predictors and hybrid deep-machine learning algorithms. Applied Energy, 316. doi:10.1016/j.apenergy.2022.119063.

Nwokolo, S. C., Obiwulu, A. U., & Ogbulezie, J. C. (2023). Machine learning and analytical model hybridization to assess the impact of climate change on solar PV energy production. Physics and Chemistry of the Earth, 130. doi:10.1016/j.pce.2023.103389.

Chukwujindu Nwokolo, S., Ogbulezie, J. C., & Umunnakwe Obiwulu, A. (2022). Impacts of climate change and meteo-solar parameters on photosynthetically active radiation prediction using hybrid machine learning with Physics-based models. Advances in Space Research, 70(11), 3614–3637. doi:10.1016/j.asr.2022.08.010.

Svazas, A.M., Navickas, V., Paskevicius, R., Bilan, Y. & Vasa, L. (2023). Renewable Energy versus Energy Security: The Impact of In-Novation on the Economy. Rynek Energii 164(1), 60-71.

Nakicenovic, N., Alcamo, J., Grubler, A., Riahi, K., Roehrl, R.A., Rogner, H.-H. , & Victor, N. (2000). Special Report on Emissions Scenarios (SRES), A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom.

Riahi, K., & Krey, V. (2023)....International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria. Available online: (accessed on June 2023).

Mester, M., A. (2015). Comparison of new RCP emission scenarios for estimating global climate change. ELTE, Budapest, Hungary. Available online: (accessed on May 2023).

He, T., Wang, D., & Qu, Y. (2017). Land surface albedo. Comprehensive Remote Sensing, 1–9, 140–162. doi:10.1016/B978-0-12-409548-9.10370-7.

Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M., & van Vuuren, D. P. P. (2011). The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109(1), 213–241. doi:10.1007/s10584-011-0156-z.

Van Vuuren, D. P., Den Elzen, M. G. J., Lucas, P. L., Eickhout, B., Strengers, B. J., Van Ruijven, B., Wonink, S., & Van Houdt, R. (2007). Stabilizing greenhouse gas concentrations at low levels: An assessment of reduction strategies and costs. Climatic Change, 81(2), 119–159. doi:10.1007/s10584-006-9172-9.

Clarke, L., Edmonds, J., Jacoby, H., Pitcher, H., Reilly, J. & Richels, R. (2007). Scenarios of Greenhouse Gas Emissions and Atmopheric Concentrations. Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological & Environmental Research, 154, Washington, United States.

Smith, S. J., & Wigley, T. M. L. (2006). Multi-gas forcing stabilization with minicam. Energy Journal, 27, 373–391. doi:10.5547/issn0195-6574-ej-volsi2006-nosi3-19.

Wise, M., Calvin, K., Thomson, A., Clarke, L., Bond-Lamberty, B., Sands, R., Smith, S. J., Janetos, A., & Edmonds, J. (2009). Implications of limiting CO2 concentrations for land use and energy. Science, 324(5931), 1183–1186. doi:10.1126/science.1168475.

Fujino, J., Nair, R., Kainuma, M., Masui, T., & Matsuoka, Y. (2006). Multi-gas mitigation analysis on stabilization scenarios using aim global model. Energy Journal, 27, 343–353. doi:10.5547/issn0195-6574-ej-volsi2006-nosi3-17.

Riahi, K., Grübler, A., & Nakicenovic, N. (2007). Scenarios of long-term socio-economic and environmental development under climate stabilization. Technological Forecasting and Social Change, 74(7), 887–935. doi:10.1016/j.techfore.2006.05.026.

Márton, Z., Szabó, B., Vad, C. F., Pálffy, K., & Horváth, Z. (2023). Environmental changes associated with drying climate are expected to affect functional groups of pro-and microeukaryotes differently in temporary saline waters. Scientific Reports, 13(1), 3243. doi:10.1186/s12302-023-00745-0.

Meteonorm (2023). Meteonorm offers unique access to the Global Energy Balance Archive Data, Meteonorm Data sources. Available online: (accessed on June 2023).

IIASA. (2009). RCP Database Version 2.0.5. International Institute for Applied Systems Analysis. Laxenburg, Austria. Available online: (accessed on June 2023).

Li, J., Li, Y., Zhu, B., & Ma, X. (2021). Analysis of hydrogen production capacity of off-grid photovoltaic system based on PVsyst software simulation. Journal of Physics: Conference Series, 2076(1), 12005. doi:10.1088/1742-6596/2076/1/012005.

Bhuvaneswari, B., D, S., & Memala, W. A. (2022). Performance Analysis of Stand-Alone Photovoltaic System Using PVsyst. ECS Transactions, 107(1), 11533–11541. doi:10.1149/10701.11533ecst.

Ready, J. F. (1997). Care and Maintenance of Lasers. Industrial Applications of Lasers, 193–214. doi:10.1016/b978-012583961-7/50008-9.

Markvart, T., & Castañer, L. (2018). Principles of solar cell operation. McEvoy’s Handbook of Photovoltaics: Fundamentals and Applications, 3–28. doi:10.1016/B978-0-12-809921-6.00001-X.

Perez, R., Ineichen, P., Seals, R., Michalsky, J., & Stewart, R. (1990). Modeling daylight availability and irradiance components from direct and global irradiance. Solar Energy, 44(5), 271–289. doi:10.1016/0038-092X(90)90055-H.

Seapan, M., Hishikawa, Y., Yoshita, M., & Okajima, K. (2020). Temperature and irradiance dependences of the current and voltage at maximum power of crystalline silicon PV devices. Solar Energy, 204, 459–465. doi:10.1016/j.solener.2020.05.019.

Meloun, M., & Militký, J. Correlation. Statistical Data Analysis, 631–666. doi:10.1533/9780857097200.631.

OMSZ (2023). The Hungarian Meteorological Service (OMSZ). OMSZ Informatics and Methodology Department, Budapest, Hungary. Available online: (accessed on June 2023).

Schaeffer, R., Szklo, A. S., Pereira de Lucena, A. F., Moreira Cesar Borba, B. S., Pupo Nogueira, L. P., Fleming, F. P., Troccoli, A., Harrison, M., & Boulahya, M. S. (2012). Energy sector vulnerability to climate change: A review. Energy, 38(1), 1–12. doi:10.1016/

Gaetani, M., Huld, T., Vignati, E., Monforti-Ferrario, F., Dosio, A., & Raes, F. (2014). The near future availability of photovoltaic energy in Europe and Africa in climate-aerosol modeling experiments. Renewable and Sustainable Energy Reviews, 38, 706–716. doi:10.1016/j.rser.2014.07.041.

Dutta, R., Chanda, K., & Maity, R. (2022). Future of solar energy potential in a changing climate across the world: A CMIP6 multi-model ensemble analysis. Renewable Energy, 188, 819–829. doi:10.1016/j.renene.2022.02.023.

Crook, J. A., Jones, L. A., Forster, P. M., & Crook, R. (2011). Climate change impacts on future photovoltaic and concentrated solar power energy output. Energy and Environmental Science, 4(9), 3101–3109. doi:10.1039/c1ee01495a.

Gernaat, D. E. H. J., de Boer, H. S., Daioglou, V., Yalew, S. G., Müller, C., & van Vuuren, D. P. (2021). Climate change impacts on renewable energy supply. Nature Climate Change, 11(2), 119–125. doi:10.1038/s41558-020-00949-9.

Full Text: PDF

DOI: 10.28991/HIJ-2024-05-01-01


  • There are currently no refbacks.

Copyright (c) 2024 Nándor Bozsik, András Szeberényi, Norbert Bozsik