Xuanyuan Wang, Xu Gao, Zhen Ji, Wei Sun, Bo Yan, Bohao Sun
{"title":"Dual-layer scheduling coordination algorithm for power supply guarantee using multi-objective optimization in spot market environment","authors":"Xuanyuan Wang, Xu Gao, Zhen Ji, Wei Sun, Bo Yan, Bohao Sun","doi":"10.1186/s42162-025-00485-w","DOIUrl":null,"url":null,"abstract":"<div><p>As the global electricity market continues to evolve, power dispatch in the spot market environment faces unprecedented challenges. Price fluctuations, the intermittency and uncertainty of renewable energy sources, and stringent environmental constraints make traditional dispatch methods inadequate. To address this, this work proposes a two-layer scheduling strategy based on a multi-objective enhanced genetic algorithm. This strategy aims at balancing multiple objectives such as cost efficiency, environmental impact, and system stability to optimize power dispatch in the spot market. The upper-layer scheduling of this strategy focuses on strategic decisions at the macro level, including generation planning and electricity market transactions. Its lower-layer scheduling concentrates on operational execution at the micro level, specifically power transmission and distribution. To validate the model’s effectiveness, this work designs a regional grid model that includes wind, solar, and several conventional generation units. The experimental results show that, compared to the benchmark strategy, the proposed algorithm achieves a cost savings of 8.33% while ensuring a reliable power supply. Additionally, the algorithm reduces carbon dioxide emissions by approximately 15.1% and significantly increases the average utilization rate of renewable energy to 93.4%. The algorithm is iterated 100 times, each simulating a 24-hour scheduling cycle. The experiment demonstrates its excellent performance in high-dimensional decision spaces and multi-objective optimization problems. This work not only provides an innovative multi-objective optimization solution for power dispatch in the spot market environment but also achieves significant improvements in terms of economic efficiency, environmental sustainability, and long-term viability. Through this two-layer scheduling strategy, the dispatch efficiency of the power system is significantly enhanced, and this provides strong support for the development of a green, low-carbon power supply system.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-025-00485-w","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-025-00485-w","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0
Abstract
As the global electricity market continues to evolve, power dispatch in the spot market environment faces unprecedented challenges. Price fluctuations, the intermittency and uncertainty of renewable energy sources, and stringent environmental constraints make traditional dispatch methods inadequate. To address this, this work proposes a two-layer scheduling strategy based on a multi-objective enhanced genetic algorithm. This strategy aims at balancing multiple objectives such as cost efficiency, environmental impact, and system stability to optimize power dispatch in the spot market. The upper-layer scheduling of this strategy focuses on strategic decisions at the macro level, including generation planning and electricity market transactions. Its lower-layer scheduling concentrates on operational execution at the micro level, specifically power transmission and distribution. To validate the model’s effectiveness, this work designs a regional grid model that includes wind, solar, and several conventional generation units. The experimental results show that, compared to the benchmark strategy, the proposed algorithm achieves a cost savings of 8.33% while ensuring a reliable power supply. Additionally, the algorithm reduces carbon dioxide emissions by approximately 15.1% and significantly increases the average utilization rate of renewable energy to 93.4%. The algorithm is iterated 100 times, each simulating a 24-hour scheduling cycle. The experiment demonstrates its excellent performance in high-dimensional decision spaces and multi-objective optimization problems. This work not only provides an innovative multi-objective optimization solution for power dispatch in the spot market environment but also achieves significant improvements in terms of economic efficiency, environmental sustainability, and long-term viability. Through this two-layer scheduling strategy, the dispatch efficiency of the power system is significantly enhanced, and this provides strong support for the development of a green, low-carbon power supply system.