{"title":"基于储能系统优化的安大略省a类客户需求费用最小化","authors":"Abdeslem Kadri, F. Mohammadi","doi":"10.1109/CCECE47787.2020.9255750","DOIUrl":null,"url":null,"abstract":"Demand charges (DC) is one of the major utility charges especially in the case of large electricity customers. The Energy Storage System (ESS) can be optimized to minimize these charges. For instance, a large consumer can minimize his DC by incorporating an ESS that charges during his low-consuming hours and discharges during his high-consuming hours. In other words, the ESS can shave the high peak powers of the customer's load profile to ensure lower DC. In this way, the large electricity customer will be able to save a big portion of his/her energy bill of which the DC is a part. This paper presents an optimization formulation for the sizing and scheduling of the ESS to minimize the energy monthly bill through the minimization of DC. Based on the market regulations of Ontario (Canada), this study investigates the potential of using the ESS for DC minimization based on real data for a large class-A Canadian electricity customer in Ontario. The results demonstrate the effectiveness of the proposed ESS deployment algorithm in minimizing the overall energy bills of the class-A customer.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Demand Charges Minimization for Ontario Class-A Customers Based on the Optimization of Energy Storage System\",\"authors\":\"Abdeslem Kadri, F. Mohammadi\",\"doi\":\"10.1109/CCECE47787.2020.9255750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Demand charges (DC) is one of the major utility charges especially in the case of large electricity customers. The Energy Storage System (ESS) can be optimized to minimize these charges. For instance, a large consumer can minimize his DC by incorporating an ESS that charges during his low-consuming hours and discharges during his high-consuming hours. In other words, the ESS can shave the high peak powers of the customer's load profile to ensure lower DC. In this way, the large electricity customer will be able to save a big portion of his/her energy bill of which the DC is a part. This paper presents an optimization formulation for the sizing and scheduling of the ESS to minimize the energy monthly bill through the minimization of DC. Based on the market regulations of Ontario (Canada), this study investigates the potential of using the ESS for DC minimization based on real data for a large class-A Canadian electricity customer in Ontario. The results demonstrate the effectiveness of the proposed ESS deployment algorithm in minimizing the overall energy bills of the class-A customer.\",\"PeriodicalId\":296506,\"journal\":{\"name\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE47787.2020.9255750\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE47787.2020.9255750","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Demand Charges Minimization for Ontario Class-A Customers Based on the Optimization of Energy Storage System
Demand charges (DC) is one of the major utility charges especially in the case of large electricity customers. The Energy Storage System (ESS) can be optimized to minimize these charges. For instance, a large consumer can minimize his DC by incorporating an ESS that charges during his low-consuming hours and discharges during his high-consuming hours. In other words, the ESS can shave the high peak powers of the customer's load profile to ensure lower DC. In this way, the large electricity customer will be able to save a big portion of his/her energy bill of which the DC is a part. This paper presents an optimization formulation for the sizing and scheduling of the ESS to minimize the energy monthly bill through the minimization of DC. Based on the market regulations of Ontario (Canada), this study investigates the potential of using the ESS for DC minimization based on real data for a large class-A Canadian electricity customer in Ontario. The results demonstrate the effectiveness of the proposed ESS deployment algorithm in minimizing the overall energy bills of the class-A customer.