Technical Performance Prediction and Employment Potential of Solar PV Systems in Cold Countries

Ephraim Bonah Agyekum, Usman Mehmood, Salah Kamel, Mokhtar Shouran, Elmazeg Elgamli and Tomiwa Adebayo ()
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Ephraim Bonah Agyekum: Department of Nuclear and Renewable Energy, Ural Federal University Named after the First President of Russia Boris Yeltsin, 19 Mira Street, 620002 Ekaterinburg, Russia
Usman Mehmood: Remote Sensing, GIS and Climatic Research Lab, National Center of GIS and Space Applications, Centre for Remote Sensing, University of the Punjab, Lahore 54590, Pakistan
Salah Kamel: Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt
Mokhtar Shouran: Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK
Elmazeg Elgamli: Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK

Sustainability, 2022, vol. 14, issue 6, 1-21

Abstract: Power distribution to decentralized and remote communities secluded from centralized grid connections has always been a problem for utilities and governments worldwide. This situation is even more critical for the isolated communities in Russia due to the vast nature of the country. Therefore, the Russian government is formulating and implementing several strategies to develop its renewable energy sector. However, very little information is available on the possible performance of solar photovoltaic (PV) modules under Russian weather conditions for all year round. Thus, this study has been designed to fill that research gap by assessing the performance ratio ( PR ), degradation, energy loss prediction, and employment potential of PV modules in the Sverdlovsk region of Russia using the PVsyst simulation model. A side-by-side comparison of the fixed tilted plane and tracking horizontal axis East–West were analyzed. According to the results, the annual production probability (P) for the fixed PV module for a P50, P75, and P90 is 39.68 MWh, 37.72 MWh, and 35.94 MWh, respectively, with a variability of 2.91 MWh. In the case of the tracking PV module, the annual production probability for the P50, P75, and P90 is 43.18 MWh, 41.05 MWh, and 39.12 MWh, respectively, with a variability of 3.17 MWh. A PR of 82.3% and 82.6% is obtained for the fixed and tracking systems, respectively, while the PV array losses for the fixed and tracking orientations are 15.1% and 14.9%, respectively. The months of May to August recorded the highest array losses due to the high temperatures that are usually recorded within that period.

Keywords: renewable energy; solar photovoltaic energy; degradation rate; PVsyst software; energy loss prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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