Danyang Li , Hongpeng Liu , Jingwei Zhang , Xu Han , Shuxin Zhang
{"title":"考虑柔性约束的高可再生能源并网新电力系统多阶段发电规划方法","authors":"Danyang Li , Hongpeng Liu , Jingwei Zhang , Xu Han , Shuxin Zhang","doi":"10.1016/j.ijepes.2025.110818","DOIUrl":null,"url":null,"abstract":"<div><div>Under the “dual-carbon” goals, the integration of high-proportion renewable energy has amplified operational uncertainties in new power systems, posing novel challenges to the economic planning of generation system expansion. However, existing power planning methodologies suffer from static modeling defects, incomplete constraint systems, and oversimplified cost structures, rendering them inadequate to support the low-carbon transition of emerging power systems. This necessitates a comprehensive consideration of system variability and flexibility to establish a multi-stage generation planning model. Addressing these limitations, this paper develops a fundamental multi-stage planning framework based on scenario tree structures, further incorporating carbon emissions and penalty costs for curtailed renewable energy. A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. The model fulfills economic-environmental requirements and ensures system reliability.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"169 ","pages":"Article 110818"},"PeriodicalIF":5.0000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multistage power generation planning approach for new power systems with high renewable energy integration considering flexibility constraints\",\"authors\":\"Danyang Li , Hongpeng Liu , Jingwei Zhang , Xu Han , Shuxin Zhang\",\"doi\":\"10.1016/j.ijepes.2025.110818\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Under the “dual-carbon” goals, the integration of high-proportion renewable energy has amplified operational uncertainties in new power systems, posing novel challenges to the economic planning of generation system expansion. However, existing power planning methodologies suffer from static modeling defects, incomplete constraint systems, and oversimplified cost structures, rendering them inadequate to support the low-carbon transition of emerging power systems. This necessitates a comprehensive consideration of system variability and flexibility to establish a multi-stage generation planning model. Addressing these limitations, this paper develops a fundamental multi-stage planning framework based on scenario tree structures, further incorporating carbon emissions and penalty costs for curtailed renewable energy. A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. The model fulfills economic-environmental requirements and ensures system reliability.</div></div>\",\"PeriodicalId\":50326,\"journal\":{\"name\":\"International Journal of Electrical Power & Energy Systems\",\"volume\":\"169 \",\"pages\":\"Article 110818\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electrical Power & Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0142061525003667\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Power & Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142061525003667","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Multistage power generation planning approach for new power systems with high renewable energy integration considering flexibility constraints
Under the “dual-carbon” goals, the integration of high-proportion renewable energy has amplified operational uncertainties in new power systems, posing novel challenges to the economic planning of generation system expansion. However, existing power planning methodologies suffer from static modeling defects, incomplete constraint systems, and oversimplified cost structures, rendering them inadequate to support the low-carbon transition of emerging power systems. This necessitates a comprehensive consideration of system variability and flexibility to establish a multi-stage generation planning model. Addressing these limitations, this paper develops a fundamental multi-stage planning framework based on scenario tree structures, further incorporating carbon emissions and penalty costs for curtailed renewable energy. A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. The model fulfills economic-environmental requirements and ensures system reliability.
期刊介绍:
The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces.
As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.