{"title":"电力系统质量分析的模拟退火优化算法:谐波和电压闪变","authors":"A. Alkandari, S. Soliman, A.H. Mantwy","doi":"10.1109/MEPCON.2008.4562403","DOIUrl":null,"url":null,"abstract":"This paper introduces new applications to Simulated Annealing (SA) optimization algorithm for measuring the voltage flicker magnitude and frequency as well as the harmonics contents of the voltage signal, for power quality analysis Moreover, the power system voltage magnitude, frequency and phase angle of the fundamental component is estimated by the proposed technique. This is a nonlinear optimization problem in continuous variables. An efficient SA algorithm with an adaptive cooling schedule and a new method for variable discretization are implemented. The new algorithm minimizes the sum of the absolute value of the error in the estimated voltage signal, and does need any approximation in modeling the voltage signal. The proposed algorithm is tested on simulated and actual recorded data. Effects of sampling frequency as well as the number of samples on the estimated parameters are discussed, ft is shown that the proposed algorithm is able to identify the parameters of the voltage signal.","PeriodicalId":236620,"journal":{"name":"2008 12th International Middle-East Power System Conference","volume":"90 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Simulated annealing optimization algorithm for electric power systems quality analysis: harmonics and voltage flickers\",\"authors\":\"A. Alkandari, S. Soliman, A.H. Mantwy\",\"doi\":\"10.1109/MEPCON.2008.4562403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces new applications to Simulated Annealing (SA) optimization algorithm for measuring the voltage flicker magnitude and frequency as well as the harmonics contents of the voltage signal, for power quality analysis Moreover, the power system voltage magnitude, frequency and phase angle of the fundamental component is estimated by the proposed technique. This is a nonlinear optimization problem in continuous variables. An efficient SA algorithm with an adaptive cooling schedule and a new method for variable discretization are implemented. The new algorithm minimizes the sum of the absolute value of the error in the estimated voltage signal, and does need any approximation in modeling the voltage signal. The proposed algorithm is tested on simulated and actual recorded data. Effects of sampling frequency as well as the number of samples on the estimated parameters are discussed, ft is shown that the proposed algorithm is able to identify the parameters of the voltage signal.\",\"PeriodicalId\":236620,\"journal\":{\"name\":\"2008 12th International Middle-East Power System Conference\",\"volume\":\"90 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 12th International Middle-East Power System Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MEPCON.2008.4562403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 12th International Middle-East Power System Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEPCON.2008.4562403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulated annealing optimization algorithm for electric power systems quality analysis: harmonics and voltage flickers
This paper introduces new applications to Simulated Annealing (SA) optimization algorithm for measuring the voltage flicker magnitude and frequency as well as the harmonics contents of the voltage signal, for power quality analysis Moreover, the power system voltage magnitude, frequency and phase angle of the fundamental component is estimated by the proposed technique. This is a nonlinear optimization problem in continuous variables. An efficient SA algorithm with an adaptive cooling schedule and a new method for variable discretization are implemented. The new algorithm minimizes the sum of the absolute value of the error in the estimated voltage signal, and does need any approximation in modeling the voltage signal. The proposed algorithm is tested on simulated and actual recorded data. Effects of sampling frequency as well as the number of samples on the estimated parameters are discussed, ft is shown that the proposed algorithm is able to identify the parameters of the voltage signal.