Analysis of Performance Yield Parameters for Selected Polycrystalline Solar Panel Brands in South Africa

Tosin Waidi Olofin (), Omowunmi Mary Longe and Tien-Chien Jen
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Tosin Waidi Olofin: Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa
Omowunmi Mary Longe: Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa
Tien-Chien Jen: Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa

Sustainability, 2023, vol. 15, issue 5, 1-18

Abstract: Electricity access is an essential factor for any nation’s fast-growing economic and technological development. Therefore, to meet the fast-growing world population, the adoption of a mix of energy sources, including renewable energy, is one of the ways to address the paucity supply of energy worldwide. In this paper, the performance yields of five solar photovoltaic (PV) modules, named PV1, PV2, PV3, PV4, and PV5, from different manufacturers were analyzed and compared to their respective cost benefits for profitable customer’s choice. The study on the panels was conducted at the geographical locations of 25.7535° S latitude and 28.2079° E longitude, with an average perimeter of 525.6 m in Pretoria, South Africa. The panels were installed without shading under the same condition of solar irradiation. The power output of each module was collected three times a day for six months. The analysis showed that the power outputs or performances of the respective modules are majorly affected by their surface temperatures as indicated by the values of multiple regression correlation of 92.9%, 96.9%, 99.1%, 97.2%, and 77.5% between the respective modules’ power outputs and temperature. The study also showed a techno-economic evaluation method that helps to economically alleviate the cost of solar PVs and balance the choice of the PV panels according to their short-term performances.

Keywords: solar photovoltaic (PV) cells; renewable energy; solar power efficiency; maximum power density; regression model; response surface methodology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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