Article(id=1221459822747239379, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, articleNumber=null, orderNo=null, doi=10.19666/j.rlfd.202211281, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1669478400000, receivedDateStr=2022-11-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1769148315368, onlineDateStr=2026-01-23, pubDate=1679673600000, pubDateStr=2023-03-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769148315368, onlineIssueDateStr=2026-01-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769148315368, creator=13701087609, updateTime=1769148315368, updator=13701087609, issue=Issue{id=1221459819031085880, tenantId=1146029695717560320, journalId=1210938733613449225, year='2023', volume='52', issue='3', pageStart='1', pageEnd='167', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769148314483, creator=13701087609, updateTime=1769149441207, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1221464544916983885, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1221464544916983886, tenantId=1146029695717560320, journalId=1210938733613449225, issueId=1221459819031085880, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=102, endPage=111, ext={EN=ArticleExt(id=1221459823019869145, articleId=1221459822747239379, tenantId=1146029695717560320, journalId=1210938733613449225, language=EN, title=Day-ahead optimal dispatching of regional integrated electric-heating operation system considering source-load interaction, columnId=1221459822952760279, journalTitle=Thermal Power Generation, columnName=Operation control and optimal scheduling technologies of wind power system, runingTitle=null, highlight=null, articleAbstract=

China's large-scale clean energy base has formed a regional power-heat combined system with multiple randomness, such as wind power, photovoltaic power generation and power/heat load, which highly depends on flexible and adjustable resources. Its low-carbon and economic operation is also challenging. In order to fully integrate the resources from source and load sides and maximize the consumption of new energy power, a day-ahead optimal dispatching method of the regional integrated electric-heating operation system considering demand response of electric, heating loads and prediction error scenario is proposed. Firstly, sliding time window multivariate Gaussian mixture distribution and Monte Carlo are used to generate and correct the random source-charge day-ahead prediction error to further optimize the forward scheduling results. Secondly, the demand response models of electric and heating loads are analogically defined. A regional electric-thermal system model considering the source-charge interaction is established. Then, considering multiple costs, a low-carbon and economic pre-ahead scheduling expectation model of the joint system is established in all typical scenarios. Finally, by taking the winter energy supply in a region in northern China as an example, the multi-scenario optimization operation results of electricity with and without electricity and heat load demand response are gradually compared. The results show that, fully introducing the electric and heating load demand responses and molten-salt thermal energy storage boiler can promote the consumption of large-scale wind and photovoltaic power, and significantly enhance the low-carbon and economic operation capability of the regional integrated electric-heating system.

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中国大型清洁能源基地形成了含风电、光伏发电、电/热负荷等多重随机性的区域电-热联合系统，灵活可调资源依赖性强，低碳、经济运行难度大。为了充分整合源、荷侧资源并最大限度消纳新能源，提出了计及电、热负荷需求响应及日前预测误差场景的区域电-热联合系统日前优化调度方法。首先，采用滑动时间窗多元高斯混合分布和蒙特卡洛对随机性源-荷日前预测误差进行场景生成和预测值修正；然后，类比定义了电、热负荷需求响应模型，建立了考虑源-荷互动的区域电-热系统模型；接着，综合考虑多重成本，在所有典型场景下建立了联合系统的低碳、经济日前优化调度期望模型；最后，以北方某地区冬季能源供给为例，渐进对比有无电、热负荷需求响应的多场景优化运行结果。结果表明，全面引入电、热负荷需求响应及电加热熔盐储热锅炉可以促进规模化风、光电力消纳，且区域电-热联合系统低碳、经济运行能力显著增强。

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胡阳（1986），男，副教授，主要研究方向为新能源发电过程建模与控制，hooyoung@ncepu.edu.cn。

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胡阳（1986），男，副教授，主要研究方向为新能源发电过程建模与控制，hooyoung@ncepu.edu.cn。

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