Yao Gnagbolou, M. Agbomahena, G. K. N'Gobi, Dr. Maurel Richy Aza-gnandji
{"title":"Climate Vulnerability of Photovoltaic Energy Systems using GIS: Case of the Plateau Department","authors":"Yao Gnagbolou, M. Agbomahena, G. K. N'Gobi, Dr. Maurel Richy Aza-gnandji","doi":"10.35940/ijeat.b3921.1212222","DOIUrl":null,"url":null,"abstract":"Benin has a large potential (3.5-5.5 kWh/m2 /day) for solar photovoltaic energy production. This daily energy production, which mainly depends on solar radiation, also varies considerably, depending on climatic parameters. The Plateau department is an industrial zone where mainly clinker and cement are mined and processed. In such an environment of dust production, meteorological data are very dynamic and act as input parameters or sometimes disruptors of the photovoltaic energy conversion chain. The aim of this paper is to determine the appropriate location of the photovoltaic field for optimal production of electrical energy, in the plateau department of Benin. The analysis is based on the multicriteria decision-making method (MCDM) and Analytic Hierarchical Process (AHP), using a Geographic Information System (GIS). ArcGIS 10.8 software was used to classify and weight the different vulnerability criteria (Global Horizontal Irradiation, Temperature, Wind Speed, Wind Direction, Precipitation, Relative Humidity, Cloud cover, and Aerosol), in order to determine the optimal photovoltaic power generation area by overlaying the layers. The result shows that solar irradiation is the most important criterion for better production of photovoltaic energy whose weight of 46.06% is the highest, and aerosol (dust), the lowest weight of 2.43%, considerably reduced energy production. The northern zone from 7°35’0″N-7°39’0″N of the commune of Ketou is therefore the best site for optimal production, considering the parameters studied.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"55 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering and Advanced Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35940/ijeat.b3921.1212222","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Benin has a large potential (3.5-5.5 kWh/m2 /day) for solar photovoltaic energy production. This daily energy production, which mainly depends on solar radiation, also varies considerably, depending on climatic parameters. The Plateau department is an industrial zone where mainly clinker and cement are mined and processed. In such an environment of dust production, meteorological data are very dynamic and act as input parameters or sometimes disruptors of the photovoltaic energy conversion chain. The aim of this paper is to determine the appropriate location of the photovoltaic field for optimal production of electrical energy, in the plateau department of Benin. The analysis is based on the multicriteria decision-making method (MCDM) and Analytic Hierarchical Process (AHP), using a Geographic Information System (GIS). ArcGIS 10.8 software was used to classify and weight the different vulnerability criteria (Global Horizontal Irradiation, Temperature, Wind Speed, Wind Direction, Precipitation, Relative Humidity, Cloud cover, and Aerosol), in order to determine the optimal photovoltaic power generation area by overlaying the layers. The result shows that solar irradiation is the most important criterion for better production of photovoltaic energy whose weight of 46.06% is the highest, and aerosol (dust), the lowest weight of 2.43%, considerably reduced energy production. The northern zone from 7°35’0″N-7°39’0″N of the commune of Ketou is therefore the best site for optimal production, considering the parameters studied.