{"title":"Carbon-aware day-ahead optimal dispatch for integrated power grid thermal systems with aggregated distributed resources","authors":"Tong Gou , Yinliang Xu , Hongbin Sun","doi":"10.1016/j.apenergy.2025.125715","DOIUrl":null,"url":null,"abstract":"<div><div>The accommodation of large-scale renewable energy and distributed resources with uncertainty and variability imposes higher flexibility requirements in integrated energy systems. This article proposes a low-carbon day-ahead optimal scheduling model for the integrated power grid thermal systems. First, the network topology and safety operation constraints of the integrated power grid thermal system are considered to ensure the economical and stable operation of the system. Second, a polyhedral based thermally controllable residential load aggregation/ disaggregation method is proposed to obtain the approximate feasible region and equivalent cost parameters of the aggregator, and the uncertainty of the parameters is modeled through distributed robust chance constraints. Third, on the basis of the theory of carbon emission flow, the carbon potential of the prescheduled power grid thermal system is analyzed to guide the development of resource scheduling strategies. Method studies with different scales of integrated power grid thermal systems were conducted, and the results showed that the proposed model can reduce carbon emissions by 8.67 % and 10.71 %, respectively, while ensuring economic benefits and safety.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"389 ","pages":"Article 125715"},"PeriodicalIF":10.1000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306261925004453","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The accommodation of large-scale renewable energy and distributed resources with uncertainty and variability imposes higher flexibility requirements in integrated energy systems. This article proposes a low-carbon day-ahead optimal scheduling model for the integrated power grid thermal systems. First, the network topology and safety operation constraints of the integrated power grid thermal system are considered to ensure the economical and stable operation of the system. Second, a polyhedral based thermally controllable residential load aggregation/ disaggregation method is proposed to obtain the approximate feasible region and equivalent cost parameters of the aggregator, and the uncertainty of the parameters is modeled through distributed robust chance constraints. Third, on the basis of the theory of carbon emission flow, the carbon potential of the prescheduled power grid thermal system is analyzed to guide the development of resource scheduling strategies. Method studies with different scales of integrated power grid thermal systems were conducted, and the results showed that the proposed model can reduce carbon emissions by 8.67 % and 10.71 %, respectively, while ensuring economic benefits and safety.
期刊介绍:
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.