{"title":"利用模型预测控制避免并网电池电压过电压","authors":"Harald Kirchsteiger, Sarah Landl","doi":"10.2478/rtuect-2023-0052","DOIUrl":null,"url":null,"abstract":"Abstract The problem of temporary overvoltage when integrating large renewable power plants into the existing grid is considered. A grid-connected battery energy storage system with an advanced predictive control algorithm is proposed to reduce the overvoltage in time periods of excessive renewable production. An approximative grid model is developed using system identification methods on regular operation data. A model predictive control algorithm utilizing predictions of load and generation determines the optimal operation strategy of the battery. A comparison in simulation between a reference case with PID control and the proposed algorithm shows a large reduction of the time spent in overvoltage conditions, especially in the case of consecutive days of high renewables production. The results suggest that energy storages combined with a predictive control strategy can effectively alleviate the overvoltage problem in renewables integration. Especially in the case when available storage capacity is comparatively low, a uniform overvoltage reduction can be realized. The method can potentially increase the PV host capacity of current grids.","PeriodicalId":46053,"journal":{"name":"Environmental and Climate Technologies","volume":"30 1","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Avoiding PV-Induced Overvoltage through Grid-Connected Batteries Using Model Predictive Control\",\"authors\":\"Harald Kirchsteiger, Sarah Landl\",\"doi\":\"10.2478/rtuect-2023-0052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The problem of temporary overvoltage when integrating large renewable power plants into the existing grid is considered. A grid-connected battery energy storage system with an advanced predictive control algorithm is proposed to reduce the overvoltage in time periods of excessive renewable production. An approximative grid model is developed using system identification methods on regular operation data. A model predictive control algorithm utilizing predictions of load and generation determines the optimal operation strategy of the battery. A comparison in simulation between a reference case with PID control and the proposed algorithm shows a large reduction of the time spent in overvoltage conditions, especially in the case of consecutive days of high renewables production. The results suggest that energy storages combined with a predictive control strategy can effectively alleviate the overvoltage problem in renewables integration. Especially in the case when available storage capacity is comparatively low, a uniform overvoltage reduction can be realized. The method can potentially increase the PV host capacity of current grids.\",\"PeriodicalId\":46053,\"journal\":{\"name\":\"Environmental and Climate Technologies\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Environmental and Climate Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/rtuect-2023-0052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental and Climate Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/rtuect-2023-0052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Avoiding PV-Induced Overvoltage through Grid-Connected Batteries Using Model Predictive Control
Abstract The problem of temporary overvoltage when integrating large renewable power plants into the existing grid is considered. A grid-connected battery energy storage system with an advanced predictive control algorithm is proposed to reduce the overvoltage in time periods of excessive renewable production. An approximative grid model is developed using system identification methods on regular operation data. A model predictive control algorithm utilizing predictions of load and generation determines the optimal operation strategy of the battery. A comparison in simulation between a reference case with PID control and the proposed algorithm shows a large reduction of the time spent in overvoltage conditions, especially in the case of consecutive days of high renewables production. The results suggest that energy storages combined with a predictive control strategy can effectively alleviate the overvoltage problem in renewables integration. Especially in the case when available storage capacity is comparatively low, a uniform overvoltage reduction can be realized. The method can potentially increase the PV host capacity of current grids.
期刊介绍:
Environmental and Climate Technologies provides a forum for information on innovation, research and development in the areas of environmental science, energy resources and processes, innovative technologies and energy efficiency. Authors are encouraged to submit manuscripts which cover the range from bioeconomy, sustainable technology development, life cycle analysis, eco-design, climate change mitigation, innovative solutions for pollution reduction to resilience, the energy efficiency of buildings, secure and sustainable energy supplies. The Journal ensures international publicity for original research and innovative work. A variety of themes are covered through a multi-disciplinary approach, one which integrates all aspects of environmental science: -Sustainability of technology development- Bioeconomy- Cleaner production, end of pipe production- Zero emission technologies- Eco-design- Life cycle analysis- Eco-efficiency- Environmental impact assessment- Environmental management systems- Resilience- Energy and carbon markets- Greenhouse gas emission reduction and climate technologies- Methodologies for the evaluation of sustainability- Renewable energy resources- Solar, wind, geothermal, hydro energy, biomass sources: algae, wood, straw, biogas, energetic plants and organic waste- Waste management- Quality of outdoor and indoor environment- Environmental monitoring and evaluation- Heat and power generation, including district heating and/or cooling- Energy efficiency.