{"title":"分布式发电的可再生能源合作管理","authors":"J. Leithon, Stefan Werner, V. Koivunen","doi":"10.23919/EUSIPCO.2018.8553316","DOIUrl":null,"url":null,"abstract":"We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by sharing renewable energy through the grid. We assume location and time dependent electricity prices, as well as parametrized transfer fees. We then formulate an optimization problem to minimize the energy cost incurred by the participating households over any specified planning horizon. The proposed strategy serves as a performance benchmark for online energy management algorithms, and can be implemented in real time by incorporating adequate forecasting techniques. We solve the optimization problem through relaxation, and use simulations to illustrate the characteristics of the solution. These simulations show that energy sharing takes place when there are differences in the load/generation and price profiles across participants. We also show that no energy sharing takes place when the load is above the local generation at all times.","PeriodicalId":303069,"journal":{"name":"2018 26th European Signal Processing Conference (EUSIPCO)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cooperative Renewable Energy Management with Distributed Generation\",\"authors\":\"J. Leithon, Stefan Werner, V. Koivunen\",\"doi\":\"10.23919/EUSIPCO.2018.8553316\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by sharing renewable energy through the grid. We assume location and time dependent electricity prices, as well as parametrized transfer fees. We then formulate an optimization problem to minimize the energy cost incurred by the participating households over any specified planning horizon. The proposed strategy serves as a performance benchmark for online energy management algorithms, and can be implemented in real time by incorporating adequate forecasting techniques. We solve the optimization problem through relaxation, and use simulations to illustrate the characteristics of the solution. These simulations show that energy sharing takes place when there are differences in the load/generation and price profiles across participants. We also show that no energy sharing takes place when the load is above the local generation at all times.\",\"PeriodicalId\":303069,\"journal\":{\"name\":\"2018 26th European Signal Processing Conference (EUSIPCO)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 26th European Signal Processing Conference (EUSIPCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/EUSIPCO.2018.8553316\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 26th European Signal Processing Conference (EUSIPCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/EUSIPCO.2018.8553316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cooperative Renewable Energy Management with Distributed Generation
We propose an energy cost minimization strategy for cooperating households equipped with renewable energy generation and storage capabilities. The participating households minimize their collective energy expenditure by sharing renewable energy through the grid. We assume location and time dependent electricity prices, as well as parametrized transfer fees. We then formulate an optimization problem to minimize the energy cost incurred by the participating households over any specified planning horizon. The proposed strategy serves as a performance benchmark for online energy management algorithms, and can be implemented in real time by incorporating adequate forecasting techniques. We solve the optimization problem through relaxation, and use simulations to illustrate the characteristics of the solution. These simulations show that energy sharing takes place when there are differences in the load/generation and price profiles across participants. We also show that no energy sharing takes place when the load is above the local generation at all times.