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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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[6] 曾子龙, 李勇, 丁心志, 等. 考虑线路动态电热特性的交直流系统分布鲁棒潮流优化策略[J]. 电工技术学报, 2024, 39(21): 6700-6719.
ZENG Z L, LI Y, DING X Z, et al.Distributionally robust power flow optimization strategy for hybrid AC/DC grids considering dynamic electro-thermal properties of lines[J]. Transactions of China Electrotechnical Society, 2024, 39(21): 6700-6719.
[7] 刘昕玥, 王果, 闵永智. 考虑可再生能源消纳的园区碳排放效益优化模型[J]. 太阳能学报, 2024, 45(6): 140-149.
LIU X Y, WANG G, MIN Y Z.Optimization model of carbon emission benefits in industrial parks considering consumption of renewable energy[J]. Acta energiae solaris sinica, 2024, 45(6): 140-149.
[8] 袁世琦, 潘鹏程, 魏业文, 等. 园区综合能源系统低碳经济优化调度模型研究[J]. 太阳能学报, 2024, 45(3): 347-356.
YUAN S Q, PAN P C, WEI Y W, et al.Study on low-carbon economic optimal scheduling model of community integrated energy system[J]. Acta energiae solaris sinica, 2024, 45(3): 347-356.
[9] 赵智勇, 李卫军, 郑秒, 等. 基于改进蜉蝣算法的光伏多峰值最大功率跟踪特性研究[J]. 太阳能学报, 2024, 45(12): 77-84.
ZHAO Z Y, LI W J, ZHENG M, et al.Research on photovoltaic multi-peak maximum power tracking characteristics based on improved mayfly algorithm[J]. Acta energiae solaris sinica, 2024, 45(12): 77-84.
[10] 栗然, 吕慧敏, 彭湘泽, 等. 考虑动态定价和碳交易的多园区综合能源服务商低碳合作优化策略[J]. 太阳能学报, 2024, 45(3): 337-346.
LI R, (LÜ/LV/LU/LYU) H M, PENG X Z, et al. Optimization strategy for low-carbon cooperation of multi-district integrated energy service providers considering dynamic pricing and carbon trading[J]. Acta energiae solaris sinica, 2024, 45(3): 337-346.
[11] 朱西平, 江强, 钟宇, 等. 计及前瞻风险的综合能源系统低碳经济调度优化[J]. 太阳能学报, 2023, 44(6): 113-121.
ZHU X P, JIANG Q, ZHONG Y, et al.Low-carbon economic dispatch optimization of integrated energy system considering forward-looking risks[J]. Acta energiae solaris sinica, 2023, 44(6): 113-121.
[12] 李帅虎, 欧阳中, 孙杰懿, 等. 面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略[J]. 太阳能学报, 2024, 45(7): 82-91.
LI S H, OUYANG Z, SUN J Y, et al.Day-ahead low-carbon dispatching strategy of power system for new energy consumption in desert, Gobi and desertification land[J]. Acta energiae solaris sinica, 2024, 45(7): 82-91.
[13] 徐博涵, 向月, 潘力, 等. 基于深度强化学习的含高比例可再生能源配电网就地分散式电压管控方法[J]. 电力系统保护与控制, 2022, 50(22): 100-109.
XU B H, XIANG Y, PAN L, et al.Local decentralized voltage management of a distribution network with a high proportion of renewable energy based on deep reinforcement learning[J]. Power system protection and control, 2022, 50(22): 100-109.
[14] 段新会, 黄嵘, 齐传杰, 等. 计及碳交易与需求响应的微能源网双层优化模型[J]. 太阳能学报, 2024, 45(3): 310-318.
DUAN X H, HUANG R, QI C J, et al.Bi-level optimization model for micro energy grid considering carbon trading and demand response[J]. Acta energiae solaris sinica, 2024, 45(3): 310-318.
[15] 葛晓琳, 余捷, 符杨, 等. 考虑源荷互动的电力系统随机碳流优化[J]. 中国电机工程学报, 2024, 44(24): 9571-9582.
GE X L, YU J, FU Y, et al.Stochastic carbon flow optimization of power system considering source-load interaction[J]. Proceedings of the CSEE, 2024, 44(24): 9571-9582.
[16] 毕瀚文, 范晓舟, 肖海, 等. 支撑电力系统全环节碳流追踪的节点导纳矩阵算法研究[J]. 中国电机工程学报, 2023, 43(20): 7881-7891.
BI H W, FAN X Z, XIAO H, et al.A node admittance matrix algorithm to support the carbon emission tracing model of whole power system[J]. Proceedings of the CSEE, 2023, 43(20): 7881-7891.)
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新型电力系统多级运行指标协同的电碳优化控制策略
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周万鹏, 李正曦, 杨立滨, 王恺
太阳能学报 | 2026,47(6): 102-108
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太阳能学报 2026 , 47 (6) : 102 -108
新型电力系统多级运行指标协同的电碳优化控制策略
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周万鹏, 李正曦, 杨立滨, 王恺
作者信息
ELECTRIC-CARBON OPTIMIZATION CONTROL STRATEGY WITH MULTI-LEVEL OPERATION INDICATOR COORDINATION IN NEW POWER SYSTEM
Zhou Wanpeng, Li Zhengxi, Yang Libin, Wang Kai
Affiliations
    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
doi: 10.19912/j.0254-0096.tynxb.2025-0172
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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。
新型电力系统  /  电碳潮流  /  协同优化  /  优化控制  /  卷积神经网络  /  运行指标
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.
new power system  /  electric-carbon flow  /  collaborative optimization  /  optimal control  /  convolutional neural network  /  operational indicators
周万鹏, 李正曦, 杨立滨, 王恺. 新型电力系统多级运行指标协同的电碳优化控制策略. 太阳能学报, 2026 , 47 (6) : 102 -108 . DOI: 10.19912/j.0254-0096.tynxb.2025-0172
Zhou Wanpeng, Li Zhengxi, Yang Libin, Wang Kai. ELECTRIC-CARBON OPTIMIZATION CONTROL STRATEGY WITH MULTI-LEVEL OPERATION INDICATOR COORDINATION IN NEW POWER SYSTEM[J]. Acta Energiae Solaris Sinica, 2026 , 47 (6) : 102 -108 . DOI: 10.19912/j.0254-0096.tynxb.2025-0172

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[5] 杨浩, 王佳怡, 易文飞, 等. 知识-数据融合驱动的配电网光伏逆变器电压/无功优化自适应控制[J]. 中国电机工程学报, 2025, 45(22): 8691-8705.
YANG H, WANG J Y, YI W F, et al.Hybrid knowledge-data driven adaptive voltage/var optimization control of photovoltaic inverters in distribution networks[J]. Proceedings of the CSEE, 2025, 45(22): 8691-8705.
[6] 曾子龙, 李勇, 丁心志, 等. 考虑线路动态电热特性的交直流系统分布鲁棒潮流优化策略[J]. 电工技术学报, 2024, 39(21): 6700-6719.
ZENG Z L, LI Y, DING X Z, et al.Distributionally robust power flow optimization strategy for hybrid AC/DC grids considering dynamic electro-thermal properties of lines[J]. Transactions of China Electrotechnical Society, 2024, 39(21): 6700-6719.
[7] 刘昕玥, 王果, 闵永智. 考虑可再生能源消纳的园区碳排放效益优化模型[J]. 太阳能学报, 2024, 45(6): 140-149.
LIU X Y, WANG G, MIN Y Z.Optimization model of carbon emission benefits in industrial parks considering consumption of renewable energy[J]. Acta energiae solaris sinica, 2024, 45(6): 140-149.
[8] 袁世琦, 潘鹏程, 魏业文, 等. 园区综合能源系统低碳经济优化调度模型研究[J]. 太阳能学报, 2024, 45(3): 347-356.
YUAN S Q, PAN P C, WEI Y W, et al.Study on low-carbon economic optimal scheduling model of community integrated energy system[J]. Acta energiae solaris sinica, 2024, 45(3): 347-356.
[9] 赵智勇, 李卫军, 郑秒, 等. 基于改进蜉蝣算法的光伏多峰值最大功率跟踪特性研究[J]. 太阳能学报, 2024, 45(12): 77-84.
ZHAO Z Y, LI W J, ZHENG M, et al.Research on photovoltaic multi-peak maximum power tracking characteristics based on improved mayfly algorithm[J]. Acta energiae solaris sinica, 2024, 45(12): 77-84.
[10] 栗然, 吕慧敏, 彭湘泽, 等. 考虑动态定价和碳交易的多园区综合能源服务商低碳合作优化策略[J]. 太阳能学报, 2024, 45(3): 337-346.
LI R, (LÜ/LV/LU/LYU) H M, PENG X Z, et al. Optimization strategy for low-carbon cooperation of multi-district integrated energy service providers considering dynamic pricing and carbon trading[J]. Acta energiae solaris sinica, 2024, 45(3): 337-346.
[11] 朱西平, 江强, 钟宇, 等. 计及前瞻风险的综合能源系统低碳经济调度优化[J]. 太阳能学报, 2023, 44(6): 113-121.
ZHU X P, JIANG Q, ZHONG Y, et al.Low-carbon economic dispatch optimization of integrated energy system considering forward-looking risks[J]. Acta energiae solaris sinica, 2023, 44(6): 113-121.
[12] 李帅虎, 欧阳中, 孙杰懿, 等. 面向沙戈荒区域新能源消纳的电力系统日前低碳调度策略[J]. 太阳能学报, 2024, 45(7): 82-91.
LI S H, OUYANG Z, SUN J Y, et al.Day-ahead low-carbon dispatching strategy of power system for new energy consumption in desert, Gobi and desertification land[J]. Acta energiae solaris sinica, 2024, 45(7): 82-91.
[13] 徐博涵, 向月, 潘力, 等. 基于深度强化学习的含高比例可再生能源配电网就地分散式电压管控方法[J]. 电力系统保护与控制, 2022, 50(22): 100-109.
XU B H, XIANG Y, PAN L, et al.Local decentralized voltage management of a distribution network with a high proportion of renewable energy based on deep reinforcement learning[J]. Power system protection and control, 2022, 50(22): 100-109.
[14] 段新会, 黄嵘, 齐传杰, 等. 计及碳交易与需求响应的微能源网双层优化模型[J]. 太阳能学报, 2024, 45(3): 310-318.
DUAN X H, HUANG R, QI C J, et al.Bi-level optimization model for micro energy grid considering carbon trading and demand response[J]. Acta energiae solaris sinica, 2024, 45(3): 310-318.
[15] 葛晓琳, 余捷, 符杨, 等. 考虑源荷互动的电力系统随机碳流优化[J]. 中国电机工程学报, 2024, 44(24): 9571-9582.
GE X L, YU J, FU Y, et al.Stochastic carbon flow optimization of power system considering source-load interaction[J]. Proceedings of the CSEE, 2024, 44(24): 9571-9582.
[16] 毕瀚文, 范晓舟, 肖海, 等. 支撑电力系统全环节碳流追踪的节点导纳矩阵算法研究[J]. 中国电机工程学报, 2023, 43(20): 7881-7891.
BI H W, FAN X Z, XIAO H, et al.A node admittance matrix algorithm to support the carbon emission tracing model of whole power system[J]. Proceedings of the CSEE, 2023, 43(20): 7881-7891.
2026年第47卷第6期
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doi: 10.19912/j.0254-0096.tynxb.2025-0172
  • 接收时间:2025-01-24
  • 首发时间:2026-07-17
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