Héricles Eduardo Oliveira Farias, Camilo Alberto Sepulveda Rangel, L. Canha, Leonardo Weber Stringini, T. A. Silva Santana, Zeno Luiz Iensen Nadal
{"title":"具有交易能源和私有聚合器的日前市场情景下的电池储能系统管理","authors":"Héricles Eduardo Oliveira Farias, Camilo Alberto Sepulveda Rangel, L. Canha, Leonardo Weber Stringini, T. A. Silva Santana, Zeno Luiz Iensen Nadal","doi":"10.1109/UPEC50034.2021.9548238","DOIUrl":null,"url":null,"abstract":"This paper presents a methodology for battery energy storage systems (BESS) management considering the concept of transactive energy. Transactive energy is defined as the economic and control technique used for energy management that allows the dynamic balance of supply and demand across the electrical system. In a transactive energy market, the consumer can produce energy and inject it into the grid, becoming a prosumer. Also, it is possible to have the presence of private aggregators. Aggregators have large energy production capacity and can negotiate this energy with the grid. The system is composed by two private aggregators, the consumers, and the distribution system operator (DSO). The aggregators are assigned to supply a specific number of consumers defined in the contractual demand with the DSO, and the DSO is responsible for serving the rest of the system. Both aggregators and the DSO have distributed energy resources (DERs), such as energy storage and/or photovoltaic generation. A neural network based on group method of data handling (GMDH) is used for forecasting the grid demand, energy prices and solar generation for the day-ahead operation. The BESS reserve for the day-ahead is optimized based on prediction model. The methodology is validated in a 33-bus distribution network simulated on software OpenDSS. The curve profiles are taken from real data of the Canadian distribution system.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Battery energy storage systems management in a day-ahead market scenario with transactive energy and private aggregators\",\"authors\":\"Héricles Eduardo Oliveira Farias, Camilo Alberto Sepulveda Rangel, L. Canha, Leonardo Weber Stringini, T. A. Silva Santana, Zeno Luiz Iensen Nadal\",\"doi\":\"10.1109/UPEC50034.2021.9548238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a methodology for battery energy storage systems (BESS) management considering the concept of transactive energy. Transactive energy is defined as the economic and control technique used for energy management that allows the dynamic balance of supply and demand across the electrical system. In a transactive energy market, the consumer can produce energy and inject it into the grid, becoming a prosumer. Also, it is possible to have the presence of private aggregators. Aggregators have large energy production capacity and can negotiate this energy with the grid. The system is composed by two private aggregators, the consumers, and the distribution system operator (DSO). The aggregators are assigned to supply a specific number of consumers defined in the contractual demand with the DSO, and the DSO is responsible for serving the rest of the system. Both aggregators and the DSO have distributed energy resources (DERs), such as energy storage and/or photovoltaic generation. A neural network based on group method of data handling (GMDH) is used for forecasting the grid demand, energy prices and solar generation for the day-ahead operation. The BESS reserve for the day-ahead is optimized based on prediction model. The methodology is validated in a 33-bus distribution network simulated on software OpenDSS. 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Battery energy storage systems management in a day-ahead market scenario with transactive energy and private aggregators
This paper presents a methodology for battery energy storage systems (BESS) management considering the concept of transactive energy. Transactive energy is defined as the economic and control technique used for energy management that allows the dynamic balance of supply and demand across the electrical system. In a transactive energy market, the consumer can produce energy and inject it into the grid, becoming a prosumer. Also, it is possible to have the presence of private aggregators. Aggregators have large energy production capacity and can negotiate this energy with the grid. The system is composed by two private aggregators, the consumers, and the distribution system operator (DSO). The aggregators are assigned to supply a specific number of consumers defined in the contractual demand with the DSO, and the DSO is responsible for serving the rest of the system. Both aggregators and the DSO have distributed energy resources (DERs), such as energy storage and/or photovoltaic generation. A neural network based on group method of data handling (GMDH) is used for forecasting the grid demand, energy prices and solar generation for the day-ahead operation. The BESS reserve for the day-ahead is optimized based on prediction model. The methodology is validated in a 33-bus distribution network simulated on software OpenDSS. The curve profiles are taken from real data of the Canadian distribution system.