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PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings

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  • Saber, Esmail M.
  • Lee, Siew Eang
  • Manthapuri, Sumanth
  • Yi, Wang
  • Deb, Chirag

Abstract

Air pollution and climate change increased the importance of renewable energy resources like solar energy in the last decades. Rack-mounted PhotoVoltaics (PV) and Building Integrated PhotoVoltaics (BIPV) are the most common photovoltaic systems which convert incident solar radiation on façade or surrounding area to electricity. In this paper the performance of different solar cell types is evaluated for the tropical weather of Singapore. As a case study, on-site measured data of PV systems implemented in a zero energy building in Singapore, is analyzed. Different types of PV systems (silicon wafer and thin film) have been installed on rooftop, façade, car park shelter, railing and etc. The impact of different solar cell generations, arrays environmental conditions (no shading, dappled shading, full shading), orientation (South, North, East or West facing) and inclination (between PV module and horizontal direction) is investigated on performance of modules. In the second stage of research, the whole PV systems in the case study are simulated in EnergyPlus energy simulation software with several PV performance models including Simple, Equivalent one-diode and Sandia. The predicted results by different models are compared with measured data and the validated model is used to provide simulation-based energy yield predictions for wide ranges of scenarios. It has been concluded that orientation of low-slope rooftop PV has negligible impact on annual energy yield but in case of PV external sunshade, east façade and panel slope of 30–40° are the most suitable location and inclination.

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  • Saber, Esmail M. & Lee, Siew Eang & Manthapuri, Sumanth & Yi, Wang & Deb, Chirag, 2014. "PV (photovoltaics) performance evaluation and simulation-based energy yield prediction for tropical buildings," Energy, Elsevier, vol. 71(C), pages 588-595.
    • Handle: RePEc:eee:energy:v:71:y:2014:i:c:p:588-595
    DOI: 10.1016/j.energy.2014.04.115
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    5. Kosorić, Vesna & Huang, Huajing & Tablada, Abel & Lau, Siu-Kit & Tan, Hugh T.W., 2019. "Survey on the social acceptance of the productive façade concept integrating photovoltaic and farming systems in high-rise public housing blocks in Singapore," Renewable and Sustainable Energy Reviews, Elsevier, vol. 111(C), pages 197-214.
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    10. Michalak, Piotr, 2014. "The simple hourly method of EN ISO 13790 standard in Matlab/Simulink: A comparative study for the climatic conditions of Poland," Energy, Elsevier, vol. 75(C), pages 568-578.
    11. Peng, Jinqing & Curcija, Dragan C. & Thanachareonkit, Anothai & Lee, Eleanor S. & Goudey, Howdy & Selkowitz, Stephen E., 2019. "Study on the overall energy performance of a novel c-Si based semitransparent solar photovoltaic window," Applied Energy, Elsevier, vol. 242(C), pages 854-872.
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    13. Mohamed Mohana & Abdelaziz Salah Saidi & Salem Alelyani & Mohammed J. Alshayeb & Suhail Basha & Ali Eisa Anqi, 2021. "Small-Scale Solar Photovoltaic Power Prediction for Residential Load in Saudi Arabia Using Machine Learning," Energies, MDPI, vol. 14(20), pages 1-18, October.
    14. Ramadan J. Mustafa & Mohamed R. Gomaa & Mujahed Al-Dhaifallah & Hegazy Rezk, 2020. "Environmental Impacts on the Performance of Solar Photovoltaic Systems," Sustainability, MDPI, vol. 12(2), pages 1-17, January.
    15. Gu, Bo & Shen, Huiqiang & Lei, Xiaohui & Hu, Hao & Liu, Xinyu, 2021. "Forecasting and uncertainty analysis of day-ahead photovoltaic power using a novel forecasting method," Applied Energy, Elsevier, vol. 299(C).
    16. Wafaa Saleh & Shekaina Justin & Ghada Alsawah & Areej Malibari & Maha M A Lashin, 2021. "An Investigation into Conversion of a Fleet of Plug-in-Electric Golf Carts into Solar Powered Vehicles Using Fuzzy Logic Control," Energies, MDPI, vol. 14(17), pages 1-13, September.
    17. Kosorić, Vesna & Lau, Siu-Kit & Tablada, Abel & Lau, Stephen Siu-Yu, 2018. "General model of Photovoltaic (PV) integration into existing public high-rise residential buildings in Singapore – Challenges and benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 70-89.
    18. Touati, Farid & Chowdhury, Noor Alam & Benhmed, Kamel & San Pedro Gonzales, Antonio J.R. & Al-Hitmi, Mohammed A. & Benammar, Mohieddine & Gastli, Adel & Ben-Brahim, Lazhar, 2017. "Long-term performance analysis and power prediction of PV technology in the State of Qatar," Renewable Energy, Elsevier, vol. 113(C), pages 952-965.
    19. Deepak Jain Veerendra Kumar & Lelia Deville & Kenneth A. Ritter & Johnathan Richard Raush & Farzad Ferdowsi & Raju Gottumukkala & Terrence Lynn Chambers, 2022. "Performance Evaluation of 1.1 MW Grid-Connected Solar Photovoltaic Power Plant in Louisiana," Energies, MDPI, vol. 15(9), pages 1-21, May.
    20. Li, Fengyun & Zheng, Haofeng & Li, Xingmei, 2022. "A novel hybrid model for multi-step ahead photovoltaic power prediction based on conditional time series generative adversarial networks," Renewable Energy, Elsevier, vol. 199(C), pages 560-586.
    21. Vesna Kosorić & Siu-Kit Lau & Abel Tablada & Monika Bieri & André M. Nobre, 2021. "A Holistic Strategy for Successful Photovoltaic (PV) Implementation into Singapore’s Built Environment," Sustainability, MDPI, vol. 13(11), pages 1-35, June.
    22. Hu, Zehuan & Gao, Yuan & Ji, Siyu & Mae, Masayuki & Imaizumi, Taiji, 2024. "Improved multistep ahead photovoltaic power prediction model based on LSTM and self-attention with weather forecast data," Applied Energy, Elsevier, vol. 359(C).
    23. Chen, X.M. & Li, Y. & Zhao, B.Y. & Wang, R.Z., 2020. "Are the optimum angles of photovoltaic systems so important?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).

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