M. Padma Lalitha, Mieee A I T S-Rajampeta, India, P. Harshavardhan, Reddy P Janardhana, Naidu A, S-Raj T Ampeta
{"title":"Generation reliability evaluation of wind energy penetrated power system","authors":"M. Padma Lalitha, Mieee A I T S-Rajampeta, India, P. Harshavardhan, Reddy P Janardhana, Naidu A, S-Raj T Ampeta","doi":"10.1109/ICHPCA.2014.7045371","DOIUrl":null,"url":null,"abstract":"This paper presents the generation adequacy evaluation of a power system with high wind energy penetration. First, the wind turbine generator unit models are developed by considering the component failure rates and uncertain nature of wind energy. The Data Synthesizer Software is used to extract the hourly wind speed values from the average seasonal data. The Fuzzy C-means Clustering Method is used to obtain the required number of generation states from the hourly data. Then the Markov process is used to obtain the probability of each generation state. Then, these wind energy models are added to the Roy Billinton Test System (RBTS) by Recursive Algorithm approach and different reliability indices are calculated.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICHPCA.2014.7045371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents the generation adequacy evaluation of a power system with high wind energy penetration. First, the wind turbine generator unit models are developed by considering the component failure rates and uncertain nature of wind energy. The Data Synthesizer Software is used to extract the hourly wind speed values from the average seasonal data. The Fuzzy C-means Clustering Method is used to obtain the required number of generation states from the hourly data. Then the Markov process is used to obtain the probability of each generation state. Then, these wind energy models are added to the Roy Billinton Test System (RBTS) by Recursive Algorithm approach and different reliability indices are calculated.
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