H. Nuha, Rizka Reza Pahlevi, M. Mohandes, S. Rehman, A. Al-Shaikhi, H. Tella
{"title":"Vertical Wind Speed Estimation Using Generalized Additive Model (GAM) for Regression","authors":"H. Nuha, Rizka Reza Pahlevi, M. Mohandes, S. Rehman, A. Al-Shaikhi, H. Tella","doi":"10.1109/CICN56167.2022.10008372","DOIUrl":null,"url":null,"abstract":"The general plan for the provision of electricity of Indonesia Electricity Company for 2010–2019 states that the annual electricity demand is 55,000 MW. Wind speed (WS) assessment is required for wind farm site candidates. This paper uses the generalized additive model (GAM) for vertical WS estimation. The method is evaluated in terms of symmetric mean absolute percentage error (SMAPE), mean absolute error (MAE), and the adjusted coefficient of determination (R2adj). The highest values of R2adj between the measured and the estimated WS values achieved by GAM method at 60, 100, 140, and 180 m of heights are 96.34%, 81.66%, 64.68 %, and 62.90 % respectively.","PeriodicalId":287589,"journal":{"name":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Computational Intelligence and Communication Networks (CICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICN56167.2022.10008372","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The general plan for the provision of electricity of Indonesia Electricity Company for 2010–2019 states that the annual electricity demand is 55,000 MW. Wind speed (WS) assessment is required for wind farm site candidates. This paper uses the generalized additive model (GAM) for vertical WS estimation. The method is evaluated in terms of symmetric mean absolute percentage error (SMAPE), mean absolute error (MAE), and the adjusted coefficient of determination (R2adj). The highest values of R2adj between the measured and the estimated WS values achieved by GAM method at 60, 100, 140, and 180 m of heights are 96.34%, 81.66%, 64.68 %, and 62.90 % respectively.