Correlation between Photovoltaic Energy Production and Certain Climate Parameters: Case Study in the Plateau Department in Southern Benin

Yao Gnagbolou, M. Agbomahena, Maurel R. Aza-Gnandji, G. K. N'Gobi
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Abstract

The Plateau department, where the first 25 MWp grid-connected solar plant was installed, is also an industrial cement zone, with high-energy demand, located in the south of Benin. In this region, the equatorial climate oscillated between two dry and two rainy seasons, with a high relative humidity. This climate variability influences the electrical output of photovoltaic (PV) modules. The analysis of the impact of climatic parameters such as relative humidity, precipitation, wind speed, ambient temperature, sunshine, on the photovoltaic production becomes necessary to optimize the energy generation in such a region. The objective of this study is to quantify the dependency relationship that exists between the variability of these parameters and the PV power generation using Pearson correlation method. The daily data collected for each parameter during the period from January 2011 to December 2020 were processed with Python 3.7.10 language. The results showed that relative humidity, with an average value of 80.14%, is the climatic has the highest negative impact (correlation coefficient of -0.42) on the performance of PV modules. Thus, the design and operation of a PV plant in this area should consider this parameter, especially with dust deposits, to improve the production yield.
光伏能源生产与某些气候参数的相关性:以贝宁南部高原地区为例
第一个25兆瓦并网太阳能发电厂安装在高原地区,该地区位于贝宁南部,也是一个高能量需求的工业水泥区。在这个地区,赤道气候在两个旱季和两个雨季之间摇摆,相对湿度很高。这种气候变化会影响光伏(PV)组件的电力输出。分析诸如相对湿度、降水、风速、环境温度、日照等气候参数对光伏发电的影响,对于优化该地区的能源生产是必要的。本研究的目的是利用Pearson相关方法量化这些参数的可变性与光伏发电之间存在的依赖关系。2011年1月至2020年12月每天采集各参数数据,使用Python 3.7.10语言进行处理。结果表明,相对湿度对光伏组件性能的负面影响最大,平均为80.14%,相关系数为-0.42。因此,该地区光伏电站的设计和运行应考虑该参数,特别是有粉尘沉积的光伏电站,以提高产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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