{"title":"以社区为基础的DSM减少峰值至平均水平","authors":"Y. Yaseen, B. Ghita","doi":"10.1109/SEGE.2017.8052798","DOIUrl":null,"url":null,"abstract":"Current power generation and distribution systems are designed for minimal peak-to-average ratio (PAR) demand, with any fluctuations leading to the addition of alternative, more expensive power generation and a significant increase in pricing for the consumers. While prior research proposed a number of solutions to reduce PAR, the issue remains topical due to the challenges in reallocating demand in a more efficient way. This paper proposes a novel Demand Side Management (DSM) which focuses on a community-based allocation of power demand for minimising the peak load. In the proposed environment, users minimise the peak-to-average ratio (PAR) of the power system by shifting consumption to off-peak times, but the policy is more effective due to the community-based nature of the demand. A daily real load profile of a user was applied to measure the performance of the proposed scheduling technique when minimising PAR, with preliminary experiments demonstrating that the method is able to successfully reduce PAR and peak load.","PeriodicalId":404327,"journal":{"name":"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Peak-to-average reduction by community-based DSM\",\"authors\":\"Y. Yaseen, B. Ghita\",\"doi\":\"10.1109/SEGE.2017.8052798\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Current power generation and distribution systems are designed for minimal peak-to-average ratio (PAR) demand, with any fluctuations leading to the addition of alternative, more expensive power generation and a significant increase in pricing for the consumers. While prior research proposed a number of solutions to reduce PAR, the issue remains topical due to the challenges in reallocating demand in a more efficient way. This paper proposes a novel Demand Side Management (DSM) which focuses on a community-based allocation of power demand for minimising the peak load. In the proposed environment, users minimise the peak-to-average ratio (PAR) of the power system by shifting consumption to off-peak times, but the policy is more effective due to the community-based nature of the demand. A daily real load profile of a user was applied to measure the performance of the proposed scheduling technique when minimising PAR, with preliminary experiments demonstrating that the method is able to successfully reduce PAR and peak load.\",\"PeriodicalId\":404327,\"journal\":{\"name\":\"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SEGE.2017.8052798\",\"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 IEEE International Conference on Smart Energy Grid Engineering (SEGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SEGE.2017.8052798","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Current power generation and distribution systems are designed for minimal peak-to-average ratio (PAR) demand, with any fluctuations leading to the addition of alternative, more expensive power generation and a significant increase in pricing for the consumers. While prior research proposed a number of solutions to reduce PAR, the issue remains topical due to the challenges in reallocating demand in a more efficient way. This paper proposes a novel Demand Side Management (DSM) which focuses on a community-based allocation of power demand for minimising the peak load. In the proposed environment, users minimise the peak-to-average ratio (PAR) of the power system by shifting consumption to off-peak times, but the policy is more effective due to the community-based nature of the demand. A daily real load profile of a user was applied to measure the performance of the proposed scheduling technique when minimising PAR, with preliminary experiments demonstrating that the method is able to successfully reduce PAR and peak load.