{"title":"Novel hydroelectricity data envelopment analysis model","authors":"K. Strang","doi":"10.1504/IJETP.2019.10021649","DOIUrl":null,"url":null,"abstract":"In this paper a data envelopment analysis (DEA) was developed using a spreadsheet to inform policy decision making for a clean renewable hydroelectricity plant located in a natural park preserve. The DEA objective function was to make the minimum changes to the proposed policy rates for hydroelectricity generation subject to the known capabilities and risks calculated from a beta distribution. The DEA decision variables were the proposed changes to the policy rates for each month. The simplex linear programming technique was used to implement DEA in a spreadsheet. Screen shots were included to illustrate how to setup the DEA spreadsheet. The results of this paper should generalise to policy makers, practitioners, analysts and researchers in the public utility and specifically in the clean renewable hydroelectricity community.","PeriodicalId":35754,"journal":{"name":"International Journal of Energy Technology and Policy","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Energy Technology and Policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJETP.2019.10021649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper a data envelopment analysis (DEA) was developed using a spreadsheet to inform policy decision making for a clean renewable hydroelectricity plant located in a natural park preserve. The DEA objective function was to make the minimum changes to the proposed policy rates for hydroelectricity generation subject to the known capabilities and risks calculated from a beta distribution. The DEA decision variables were the proposed changes to the policy rates for each month. The simplex linear programming technique was used to implement DEA in a spreadsheet. Screen shots were included to illustrate how to setup the DEA spreadsheet. The results of this paper should generalise to policy makers, practitioners, analysts and researchers in the public utility and specifically in the clean renewable hydroelectricity community.