New models for the influence of rainwater on the performance of photovoltaic modules under different rainfall conditions
Wanxiang Yao,
Xiangru Kong,
Ai Xu,
Puyan Xu,
Yan Wang and
Weijun Gao
Renewable and Sustainable Energy Reviews, 2023, vol. 173, issue C
Abstract:
Solar photovoltaic (PV) technology is considered one of the most promising clean energy technologies. Dust accumulation on the surface of photovoltaic modules is one of the important reasons for the decline of photovoltaic system performance, and the influence of rainfall is particularly significant. The purpose of this paper is to investigate the influence of rainwater on the output power of photovoltaic modules under different rainfall conditions. In this paper, a prediction model for dust density under different inclination angles is established based on outdoor test data, and the control variable method is used to design three different PV module performance testing schemes under different rainfall conditions, and a dimensionless model for output power is proposed. Empirical models of global solar radiation are combined, and thus output power prediction models under different rainfall conditions are developed. It is found that rainstorm conditions (Rainfall 50–100 mm) increased the peak PV module output power by 16.1%–28.2% compared to light rainfall conditions (Rainfall less than 10 mm), with the rain showing better cleaning effects for PV modules with higher dust densities. It is worth noting that PV module surface dust does not necessarily have only a negative effect on system performance. The influence mechanism of rainwater on the output power of photovoltaic modules and the prediction model established in this paper is helpful in improving the prediction accuracy of the output power of photovoltaic modules under rainfall conditions, and thus the efficient cleaning strategy is formulated.
Keywords: Rainfall; Dust density; Photovoltaic module performance; Output power; Prediction model (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (4)
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DOI: 10.1016/j.rser.2022.113119
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