R. Petrichenko, L. Petrichenko, K. Baltputnis, A. Sauhats, S. Gudzius, Aivaras Slivikas
{"title":"在储能系统管理任务中,规划周期初始状态和时间段的选择","authors":"R. Petrichenko, L. Petrichenko, K. Baltputnis, A. Sauhats, S. Gudzius, Aivaras Slivikas","doi":"10.1109/RTUCON51174.2020.9316613","DOIUrl":null,"url":null,"abstract":"The large-scale use of renewable energy sources and combined heat and power plants and the unstable, poorly controlled nature of consumption aggravate the problem of energy storage. When designing and operating storage plants, the task is to ensure their profitability. Usually optimization tasks are formulated with the goal of maximizing profits. When solving these problems, significant difficulties may arise, since in the general case they are nonlinear, stochastic, multistage and contain a large number of decision and state variables. This article is devoted to the problem of ensuring acceptable accuracy and time spent on maximizing profits of pumped storage hydropower plants. Based on an analysis based on the data from a real power plant, Nord Pool electricity price records and mixed integer linear programming, the dependence of the optimisation results on the initial state of the reservoirs and the duration of the planning period is shown. The results can be used both when controlling real stations and at the stage of their feasibility study.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Selection of the initial state and duration of the planning period in the tasks of managing energy storage systems\",\"authors\":\"R. Petrichenko, L. Petrichenko, K. Baltputnis, A. Sauhats, S. Gudzius, Aivaras Slivikas\",\"doi\":\"10.1109/RTUCON51174.2020.9316613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The large-scale use of renewable energy sources and combined heat and power plants and the unstable, poorly controlled nature of consumption aggravate the problem of energy storage. When designing and operating storage plants, the task is to ensure their profitability. Usually optimization tasks are formulated with the goal of maximizing profits. When solving these problems, significant difficulties may arise, since in the general case they are nonlinear, stochastic, multistage and contain a large number of decision and state variables. This article is devoted to the problem of ensuring acceptable accuracy and time spent on maximizing profits of pumped storage hydropower plants. Based on an analysis based on the data from a real power plant, Nord Pool electricity price records and mixed integer linear programming, the dependence of the optimisation results on the initial state of the reservoirs and the duration of the planning period is shown. The results can be used both when controlling real stations and at the stage of their feasibility study.\",\"PeriodicalId\":332414,\"journal\":{\"name\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTUCON51174.2020.9316613\",\"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 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Selection of the initial state and duration of the planning period in the tasks of managing energy storage systems
The large-scale use of renewable energy sources and combined heat and power plants and the unstable, poorly controlled nature of consumption aggravate the problem of energy storage. When designing and operating storage plants, the task is to ensure their profitability. Usually optimization tasks are formulated with the goal of maximizing profits. When solving these problems, significant difficulties may arise, since in the general case they are nonlinear, stochastic, multistage and contain a large number of decision and state variables. This article is devoted to the problem of ensuring acceptable accuracy and time spent on maximizing profits of pumped storage hydropower plants. Based on an analysis based on the data from a real power plant, Nord Pool electricity price records and mixed integer linear programming, the dependence of the optimisation results on the initial state of the reservoirs and the duration of the planning period is shown. The results can be used both when controlling real stations and at the stage of their feasibility study.