Article(id=1284794222414905365, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, articleNumber=null, orderNo=null, doi=10.19912/j.0254-0096.tynxb.2025-0172, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1737648000000, receivedDateStr=2025-01-24, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1784248412946, onlineDateStr=2026-07-17, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1784248412946, onlineIssueDateStr=2026-07-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1784248412946, creator=13701087609, updateTime=1784248412946, updator=13701087609, issue=Issue{id=1284794217658560734, tenantId=1146029695717560320, journalId=1283840536528293913, year='2026', volume='47', issue='6', pageStart='1', pageEnd='814', issueExtLink='null', onlineDate='null', pubDate='1783180800000', pubDateStr='2026-07-05', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1784248411812, creator='13701087609', updateTime=1784252840208, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1284812791785689442, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1284812791785689443, tenantId=1146029695717560320, journalId=1283840536528293913, issueId=1284794217658560734, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=102, endPage=108, ext={EN=ArticleExt(id=1284794222779809815, articleId=1284794222414905365, tenantId=1146029695717560320, journalId=1283840536528293913, language=EN, title=ELECTRIC-CARBON OPTIMIZATION CONTROL STRATEGY WITH MULTI-LEVEL OPERATION INDICATOR COORDINATION IN NEW POWER SYSTEM, columnId=null, journalTitle=Acta Energiae Solaris Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=In view of the characteristics of multi-regional correlation of full-network power flow in the new-type power system, an optimization method for coordinated electricity-carbon operation and a new full-network multi-regional cooperative optimization method for dynamically matching coordinated electricity-carbon operation are proposed. Firstly, according to the characteristics of cascade multi-source load-storage units in sub-regions of the new-type power system, the differences in operational regulation efficiency of various load-storage units within the region are analyzed, and a gradient cooperative optimization method for load-storage unit indicators is proposed. Then, aiming at the diversified characteristics of electricity-carbon regulation of load-storage units under different operating modes, a fine-tuning optimization method for load-storage unit control parameters based on complete state space and operational mode feedback is studied, and a 'multi-level multi-core' convolutional neural network model is established. Finally, a simulation model is constructed for validation. Simulation results show that the proposed multi-level indicator cooperative electricity-carbon power flow optimization control strategy can effectively enhance the electricity-carbon coordination capability and electricity-carbon regulation level of the new-type power system., authors=Zhou Wanpeng, Li Zhengxi, Yang Libin, Wang Kai, authorsList=Zhou Wanpeng, Li Zhengxi, Yang Libin, Wang Kai, authorCompany=1. State Grid Qinghai Electric Power Company Economic and Technological Research Institute, Xining 810008, China;
2. State Grid Qinghai Electric Power Company Clean Energy Development Research Institute, Xining 810008, China;
3. State Grid Qinghai Electric Power Company, Xining 810008, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1284794222708506646, articleId=1284794222414905365, tenantId=1146029695717560320, journalId=1283840536528293913, language=CN, title=新型电力系统多级运行指标协同的电碳优化控制策略, columnId=null, journalTitle=太阳能学报, columnName=null, runingTitle=null, highlight=null, articleAbstract=针对新型电力系统全网潮流多区域关联的特点,提出电碳协同运行方式优化方法和电碳协同运行方式动态匹配的新型电力系统全网潮流多区域协同优化方法。首先,根据新型电力系统子区域多源荷储单元级联的特点,分析区域内不同源荷储单元的运行调节效率差异,提出源荷储单元指标梯度协同优化方法。然后,针对源荷储单元电碳调节特性在不同运行方式下多样化的特点,研究基于完备状态空间与运行方式反馈的源荷储单元调控参数精细化优化方法,建立“多重-多核”卷积神经网络模型。最后,搭建仿真模型进行验证,仿真结果表明提出的多级指标协同的电碳潮流优化控制策略能有效提升新型电力系统电碳协调能力及电碳调节水平。, authors=周万鹏, 李正曦, 杨立滨, 王恺, authorsList=周万鹏, 李正曦, 杨立滨, 王恺, authorCompany=1.国网青海省电力公司经济技术研究院,西宁 810008;
2.国网青海省电力公司清洁能源发展研究院,西宁 810008;
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