{"title":"基于有效性概念和模糊卡尔曼滤波的节能降压评估平台","authors":"F. Sabahi","doi":"10.1109/ICCKE.2017.8167944","DOIUrl":null,"url":null,"abstract":"Improving electric energy conservation has been a topic of interest to the electric power industry for a long time. Conservation Voltage Reduction (CVR) is a proven method for saving energy and reducing peak demand. However, due to highly stochastic load behavior and increasing the market penetration by intermittent renewable energies, energy conservation remains a challenge. We propose an improved CVR assessment scheme that employs a fuzzy Kalman filter with load-to-voltage (LTV) dependence while manipulating with the degree of validity to deal with this challenge. By definition, in the proposed approach, the fuzzy Kalman filter is used to estimate time-varying model parameters, while manipulation with validity concept leveraging human expert knowledge to increase the efficiency of the filter. Simulation results on an IEEE 34-bus, 24.9 kV test feeder show the priority of the proposed approach compared with alternative approaches.","PeriodicalId":151934,"journal":{"name":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A novel platform of validity concept and fuzzy Kalman filter applied to conservation voltage reduction assessment\",\"authors\":\"F. Sabahi\",\"doi\":\"10.1109/ICCKE.2017.8167944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Improving electric energy conservation has been a topic of interest to the electric power industry for a long time. Conservation Voltage Reduction (CVR) is a proven method for saving energy and reducing peak demand. However, due to highly stochastic load behavior and increasing the market penetration by intermittent renewable energies, energy conservation remains a challenge. We propose an improved CVR assessment scheme that employs a fuzzy Kalman filter with load-to-voltage (LTV) dependence while manipulating with the degree of validity to deal with this challenge. By definition, in the proposed approach, the fuzzy Kalman filter is used to estimate time-varying model parameters, while manipulation with validity concept leveraging human expert knowledge to increase the efficiency of the filter. Simulation results on an IEEE 34-bus, 24.9 kV test feeder show the priority of the proposed approach compared with alternative approaches.\",\"PeriodicalId\":151934,\"journal\":{\"name\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCKE.2017.8167944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Computer and Knowledge Engineering (ICCKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCKE.2017.8167944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A novel platform of validity concept and fuzzy Kalman filter applied to conservation voltage reduction assessment
Improving electric energy conservation has been a topic of interest to the electric power industry for a long time. Conservation Voltage Reduction (CVR) is a proven method for saving energy and reducing peak demand. However, due to highly stochastic load behavior and increasing the market penetration by intermittent renewable energies, energy conservation remains a challenge. We propose an improved CVR assessment scheme that employs a fuzzy Kalman filter with load-to-voltage (LTV) dependence while manipulating with the degree of validity to deal with this challenge. By definition, in the proposed approach, the fuzzy Kalman filter is used to estimate time-varying model parameters, while manipulation with validity concept leveraging human expert knowledge to increase the efficiency of the filter. Simulation results on an IEEE 34-bus, 24.9 kV test feeder show the priority of the proposed approach compared with alternative approaches.