电碳耦合视角下新型电力系统低碳运行调度的关键问题及展望

赵俊华; 白焰; 王智冬

doi:10.12204/j.issn.1000-7229.2025.07.011

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电力建设 ›› 2025, Vol. 46 ›› Issue (7) : 133-149. DOI: 10.12204/j.issn.1000-7229.2025.07.011

调度运行

电碳耦合视角下新型电力系统低碳运行调度的关键问题及展望

赵俊华 ¹^,² ,
白焰 ¹ ,
王智冬 ³

作者信息 +

Key Issues and Prospects for Low-Carbon Operation and Scheduling of the New Power System from an Electricity-Carbon Coupling Perspective

ZHAO Junhua ¹^,² ,
BAI Yan ¹ ,
WANG Zhidong ³

Author information +

文章历史 +

摘要

【目的】新型电力系统的发展为我国推动电力系统低碳转型指明了方向，但其安全、经济与低碳三大目标使其运行调度面临着 “能源不可能三角”难题。随着电力市场和碳排放市场的相继成熟和一体化发展，传统的电力调度模式正在发生革新，构建适用于新型电力系统运行调度的市场体系将成为解决其低碳电力调度难题的关键一环。【方法】文章基于电碳耦合的视角，厘清了电力市场和碳排放市场的交互影响，研究了电力-碳排放双重市场下新型电力系统的低碳运行调度策略和市场机制问题。具体而言，文章从碳排放感知、市场主体行为建模、电-碳市场联合仿真、低碳调度策略以及新型电力系统市场机制五个方面，开展了广泛调研和系统综述，剖析了低碳运行调度的五大关键技术和研究局限。【结果】结果表明，现有研究在上述关键维度均存在短板。特别是在电‐碳市场一体化进程中，耦合机制不明和配额机制缺失使协同机制显得静态且过于简化，市场仿真方法存在可解释性不足与过强假设的矛盾；同时，可再生能源（近零短期边际成本）机组入市引发传统定价模式失效和多时段成本分摊难题。【结论】针对这些挑战，文章提出了面向新型电力系统低碳调度问题的研究框架，致力在完善碳感知体系与市场建模仿真方法基础上探索新能源主导下的低碳运行新路径，为相关领域研究提供新的视角和思考。

Abstract

[Objective] The development of a new power system has paved the way for promoting a low-carbon transition in power grids in China. However， the simultaneous pursuit of safety， economic efficiency， and low-carbon emissions poses an “energy trilemma” in system operations and dispatch. As electricity and carbon markets mature and integrate， traditional dispatch methods are being reformed， making the establishment of a market mechanism tailored to new power systems pivotal for addressing low-carbon dispatch challenges.[Methods] From the perspective of electro-carbon coupling， this study clarifies the interactive impact between electricity and carbon markets. It investigates low-carbon operational strategies and market mechanism designs within dual electricity-carbon markets for the new power system. Specifically， a comprehensive survey and systematic review are conducted in five areas： carbon emission awareness， market participant behavior modeling， joint simulation of electricity and carbon markets， low-carbon dispatch strategies， and market mechanisms for new power systems， thereby dissecting the five key technologies for low-carbon dispatch along with their research limitations.[Results] The findings revealed that the existing research had deficiencies in the aforementioned dimensions. In particular， during the integration of the electricity and carbon markets， unclear coupling mechanisms and the absence of an effective quota allocation mechanism rendered the market coordination process static and overly simplified. Moreover， market simulation methods faced a contradiction between insufficient interpretability and overly stringent assumptions， and the integration of renewable energy units （characterized by near-zero short-term marginal costs） undermined traditional pricing models and complicated multi-period cost allocation.[Conclusions] To address these challenges， this study proposes a research framework for low-carbon dispatch in the new power system. The framework is geared towards exploring renewable-energy-dominated low-carbon operational pathways based on enhanced carbon sensing and improved market modeling and simulation methods， thus offering fresh perspectives and insights for the low-carbon transformation of power systems.

导出引用

赵俊华, 白焰, 王智冬. 电碳耦合视角下新型电力系统低碳运行调度的关键问题及展望[J]. 电力建设. 2025, 46(7): 133-149 https://doi.org/10.12204/j.issn.1000-7229.2025.07.011

ZHAO Junhua, BAI Yan, WANG Zhidong. Key Issues and Prospects for Low-Carbon Operation and Scheduling of the New Power System from an Electricity-Carbon Coupling Perspective[J]. Electric Power Construction. 2025, 46(7): 133-149 https://doi.org/10.12204/j.issn.1000-7229.2025.07.011

中图分类号： TM73

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]	周太东, 王泺, 施训鹏. 能源清洁转型与全球发展路径[J]. 全球能源互联网, 2024, 7(6): 627-628. ZHOU Taidong, WANG Luo, SHI Xunpeng. Clean energy transformation and global development path[J]. Journal of Global Energy Interconnection, 2024, 7(6): 627-628. 本文引用 [1]

[2]

习近平在第七十五届联合国大会一般性辩论上的讲话[EB/OL].(2020-09-22)[2024-06-10]. https://baijiahao.baidu.com/s?id=1678547030736655301&wfr=spider&for=pc.

https://baijiahao.baidu.com/s?id=1678547030736655301&wfr=spider&for=pc

Statement by Xi Jinping at the general debate of the 75th session of the United Nations General Assembly[EB/OL].(2020-09-22)[2024-06-10]. https://baijiahao.baidu.com/s?id=1678547030736655301&wfr=spider&for=pc.

https://baijiahao.baidu.com/s?id=1678547030736655301&wfr=spider&for=pc

本文引用 [1]

[3]	新华社. 习近平主持召开中央财经委员会第九次会议[J]. 预算管理与会计, 2021(4): 4-5. XINHUA News Agency. Xi Jinping presides over the ninth meeting of the Central Committee for Financial and Economic Affairs[J]. Budget Management & Accounting, 2021(4): 4-5. 本文引用 [1]

[4]

国家能源局综合司关于公开征求《新型电力系统发展蓝皮书(征求意见稿)》意见的通知[EB/OL].(2023-01-04)[2024-06-10]. http://www.nea.gov.cn/2023-01/06/c_1310688702.htm.

http://www.nea.gov.cn/2023-01/06/c_1310688702.htm

Notice from the Comprehensive Department of the National Energy Administration on publicly soliciting opinions on the draft of the “blue book on the development of new power system” [EB/OL]. (2023-01-04)[2024-06-10]. http://www.nea.gov.cn/2023-01/06/c_1310688702.htm.

http://www.nea.gov.cn/2023-01/06/c_1310688702.htm

本文引用 [1]

[5]	HEFFRON R J, MCCAULEY D, DE RUBENS G Z. Balancing the energy trilemma through the energy justice metric[J]. Applied Energy, 2018, 229: 1191-1201. 本文引用 [1]

[6]	高志远, 陈亚军, 孙芊, 等. 电力计划和市场双轨制运行中部分协调问题探讨[J]. 供用电, 2023, 40(4): 83-91. GAO Zhiyuan, CHEN Yajun, SUN Qian, et al. Discussion on some coordination problems in the dual-track operation of power planning and market[J]. Distribution & Utilization, 2023, 40(4): 83-91. 本文引用 [1]

[7]	张智刚, 康重庆. 碳中和目标下构建新型电力系统的挑战与展望[J]. 中国电机工程学报, 2022, 42(8): 2806-2819. ZHANG Zhigang, KANG Chongqing. Challenges and prospects for constructing the new-type power system towards a carbon neutrality future[J]. Proceedings of the CSEE, 2022, 42(8): 2806-2819. 本文引用 [2]

[8]

2022年二季度全国新能源电力消纳评估分析[EB/OL].(2022-09-07)[2024-06-10]. https://news.bjx.com.cn/html/20220907/1253622.shtml.

https://news.bjx.com.cn/html/20220907/1253622.shtml

National new energy power consumption assessment and analysis for the second quarter of 2022[EB/OL]. (2022-09-07)[2024-06-10]. https://news.bjx.com.cn/html/20220907/1253622.shtml.

https://news.bjx.com.cn/html/20220907/1253622.shtml

本文引用 [1]

[9]	周业荣, 毛玉鑫, 胡杨, 等. 2022年夏季极端天气对四川电力影响与启示[J]. 水力发电学报, 2023, 42(6): 23-29. ZHOU Yerong, MAO Yuxin, HU Yang, et al. Impacts of extreme weather on Sichuan power in summer of 2022 and its enlightenment[J]. Journal of Hydroelectric Engineering, 2023, 42(6): 23-29. 本文引用 [1]

[10]	程松, 周鑫, 任景, 等. 面向新型能源体系的电力市场机制发展趋势研究[J]. 广东电力, 2023, 36(11): 29-40. CHENG Song, ZHOU Xin, REN Jing, et al. Research on the trend of electricity market mechanism for new energy system[J]. Guangdong Electric Power, 2023, 36(11): 29-40. 本文引用 [1]

[11]	李祥光, 谭青博, 李帆琪, 等. 电碳耦合对煤电机组现货市场结算电价影响分析模型[J]. 中国电力, 2024, 57(5): 113-125. LI Xiangguang, TAN Qingbo, LI Fanqi, et al. Analysis model to study the influence of electrocarbon coupling on settlement price of coal power units in spot market[J]. Electric Power, 2024, 57(5): 113-125. 本文引用 [1]

[12]	NASSAR R, HILL T G, MCLINDEN C A, et al. Quantifying CO₂ emissions from individual power plants from space[J]. Geophysical Research Letters, 2017, 44(19): 10045-10053. 本文引用 [1]

[13]	ZHENG B, CHEVALLIER F, CIAIS P, et al. Observing carbon dioxide emissions over China’s cities and industrial areas with the orbiting carbon observatory-2[J]. Atmospheric Chemistry and Physics, 2020, 20(14): 8501-8510. 本文引用 [1]

[14]	SHAW J T, SHAH A, YONG H, et al. Methods for quantifying methane emissions using unmanned aerial vehicles: a review[J]. Philosophical Transactions Series A, Mathematical, Physical, and Engineering Sciences, 2021, 379(2210): 20200450. 本文引用 [1]

[15]	SALAS-NAVARRO J, STIX J, DE MOOR J M. A new Multi-GAS system for continuous monitoring of CO₂/CH₄ ratios at active volcanoes[J]. Journal of Volcanology and Geothermal Research, 2022, 426: 107533. 本文引用 [1]

[16]	REUTER M, BUCHWITZ M, BOVENSMANN H, et al. UAV based measurements of CO₂ emissions from anthropogenic point sources[C]// EGU General Assembly Conference, 2020: 1641. 本文引用 [1]

[17]	FRANKENBERG C, POLLOCK R, LEE R A M, et al. The orbiting carbon observatory (OCO-2): spectrometer performance evaluation using pre-launch direct Sun measurements[J]. Atmospheric Measurement Techniques, 2015, 8(1): 301-313. 本文引用 [1]

[18]	PHANG S K, CHIANG T H A, HAPPONEN A, et al. From satellite to UAV-based remote sensing: a review on precision agriculture[J]. IEEE Access, 2023, 11: 127057-127076. 本文引用 [1]

[19]	JI L, LIANG S, QU S, et al. Greenhouse gas emission factors of purchased electricity from interconnected grids[J]. Applied Energy, 2016, 184: 751-758. 本文引用 [1]

[20]	LIU G L, LIU J J, ZHAO J H, et al. Real-time corporate carbon footprint estimation methodology based on appliance identification[J]. IEEE Transactions on Industrial Informatics, 2023, 19(2): 1401-1412. 本文引用 [1]

[21]	KANG C Q, ZHOU T R, CHEN Q X, et al. Carbon emission flow from generation to demand: a network-based model[J]. IEEE Transactions on Smart Grid, 2015, 6(5): 2386-2394. 本文引用 [1]

[22]	曾金灿, 王成围, 杨晨, 等. 基于广义节点碳流理论的区域电网用电碳排放计算方法[J]. 广东电力, 2023, 36(11): 20-28. ZENG Jincan, WANG Chengwei, YANG Chen, et al. Measurement method of area electricity carbon emission based on generalized nodal carbon emission flow[J]. Guangdong Electric Power, 2023, 36(11): 20-28. 本文引用 [1]

[23]	翟绘景, 高梓淳, 李文静, 等. 计及网损和相关性的新型电力系统概率碳排放流计算[J]. 供用电, 2024, 41(7): 84-91. ZHAI Huijing, GAO Zichun, LI Wenjing, et al. Calculation of probabilistic carbon emission flow in a new power system considering network losses and correlation[J]. Distribution & Utilization, 2024, 41(7): 84-91. 本文引用 [1]

[24]	程祥, 李林芝, 吴浩, 等. 非侵入式负荷监测与分解研究综述[J]. 电网技术, 2016, 40(10): 3108-3117. CHENG Xiang, LI Linzhi, WU Hao, et al. A survey of the research on non-intrusive load monitoring and disaggregation[J]. Power System Technology, 2016, 40(10): 3108-3117. 本文引用 [1]

[25]	李鹏, 吴文昊, 郭伟. 连续监测方法在全国碳市场应用的挑战与对策[J]. 环境经济研究, 2021, 6(1): 77-92. LI Peng, WU Wenhao, GUO Wei. The challenges and recommendations of application of the measurement-based monitoring methodology in national carbon market[J]. Journal of Environmental Economics, 2021, 6(1): 77-92. 本文引用 [1]

[26]	PANDEY D, AGRAWAL M, PANDEY J S. Carbon footprint: current methods of estimation[J]. Environmental Monitoring and Assessment, 2011, 178(1/2/3/4): 135-160. 本文引用 [1]

[27]	李光肖, 杨依路, 刘宗杰, 等. 基于扩展系统动力学模型的电力碳排放量预测方法[J]. 山东电力技术, 2024, 51(11): 61-73. LI Guangxiao, YANG Yilu, LIU Zongjie, et al. Carbon emission prediction method for power sector based on extended system dynamics model[J]. Shandong Electric Power, 2024, 51(11): 61-73. 本文引用 [1]

[28]	张宇娇, 李宏松, 郭垚, 等. 电缆支架全生命周期碳排放计算与分析[J]. 高压电器, 2024, 60(4): 40-48. ZHANG Yujiao, LI Hongsong, GUO Yao, et al. Calculation and analysis of carbon emission of cable bracket during its whole life cycle[J]. High Voltage Apparatus, 2024, 60(4): 40-48. 本文引用 [1]

[29]	HOFFMANN S, LASAROV W, REIMERS H. Carbon footprint tracking apps. what drives consumers' adoption intention?[J]. Technology in Society, 2022, 69: 101956. 本文引用 [1]

[30]	王微, 林剑艺, 崔胜辉, 等. 碳足迹分析方法研究综述[J]. 环境科学与技术, 2010, 33(7): 71-78. WANG Wei, LIN Jianyi, CUI Shenghui, et al. An overview of carbon footprint analysis[J]. Environmental Science & Technology, 2010, 33(7): 71-78. 本文引用 [1]

[31]	GUZMAN L, MAKONIN S, CLAPP A. CarbonKit: designing a personal carbon tracking platform[C]// Proceedings of the Fourth International Workshop on Social Sensing. ACM, 2019: 24-29. 本文引用 [1]

[32]	BUGLIESI M, PRENEEL B, SASSONE V, et al. Automata, languages and programming: 33rd international colloquium, ICALP 2006, Venice, Italy, July 10-14, 2006, Proceedings, Part II[M]. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006 本文引用 [1]

[33]	WILLCOX S, MEINIG C, SABINE C L, et al. An autonomous mobile platform for underway surface carbon measurements in open-ocean and coastal waters[C]// OCEANS 2009. IEEE, 2009: 1-8. 本文引用 [1]

[34]	冯登国, 张敏, 李昊. 大数据安全与隐私保护[J]. 计算机学报, 2014, 37(1): 246-258. FENG Dengguo, ZHANG Min, LI Hao. Big data security and privacy protection[J]. Chinese Journal of Computers, 2014, 37(1): 246-258. 本文引用 [1]

[35]

HUI

H W

, ZHOU

C C

, XU

S G

, et al. A novel secure data transmission scheme in industrial Internet of Things[J]. China Communications, 2020, 17(1): 73-88.

本文引用 [1] 摘要

The industrial Internet of Things (IoT) is a trend of factory development and a basic condition of intelligent factory. It is very important to ensure the security of data transmission in industrial IoT. Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper. The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order. The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system. The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle. We calculate and analyze the key space of the scheme. Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.

[36]	张丽丽, 张玉清. 基于分布式计算的RC4加密算法的暴力破解[J]. 计算机工程与科学, 2008, 30(7): 15-17, 20. ZHANG Lili, ZHANG Yuqing. Brute force attack on the RC4 encryption algorithm based on distributed computing[J]. Computer Engineering & Science, 2008, 30(7): 15-17, 20. 本文引用 [1]

[37]	MCMAHAN H B, MOORE E, RAMAGE D, et al. Communication-efficient learning of deep networks from decentralized data[EB/OL]. 2016: 1602.05629. https://arxiv.org/abs/1602.05629v4. https://arxiv.org/abs/1602.05629v4 本文引用 [1]

[38]	PÖTTER H, LEE S, MOSSÉ D. Towards privacy-preserving framework for non-intrusive load monitoring[C]// Proceedings of the Twelfth ACM International Conference on Future Energy Systems. ACM, 2021: 259-263. 本文引用 [1]

[39]	DIMITROV D I, BALUNOVIC M, KONSTANTINOV N, et al. Data leakage in federated averaging[J]. Transactions on Machine Learning Research, 2022:1-24. 本文引用 [1]

[40]	WEI K, LI J, DING M, et al. Federated learning with differential privacy: algorithms and performance analysis[J]. IEEE Transactions on Information Forensics and Security, 2020, 15: 3454-3469. 本文引用 [1]

[41]	PHONG L T, AONO Y, HAYASHI T, et al. Privacy-preserving deep learning via additively homomorphic encryption[J]. IEEE Transactions on Information Forensics and Security, 2018, 13(5): 1333-1345. 本文引用 [1]

[42]	LI Y, FENG T T, LIU L L, et al. How do the electricity market and carbon market interact and achieve integrated development? : a bibliometric-based review[J]. Energy, 2023, 265: 126308. 本文引用 [1]

[43]	林伯强. 现代能源体系下的碳市场与电力市场协调发展[J]. 人民论坛·学术前沿, 2022(13): 56-65. LIN Boqiang. Coordinated development of carbon market and electricity market under modern energy system[J]. Frontiers, 2022(13): 56-65. 本文引用 [1]

[44]	GAO Y N, LI M, XUE J J, et al. Evaluation of effectiveness of China’s carbon emissions trading scheme in carbon mitigation[J]. Energy Economics, 2020, 90: 104872. 本文引用 [1]

[45]	ZHANG X H, GAN D M, WANG Y L, et al. The impact of price and revenue floors on carbon emission reduction investment by coal-fired power plants[J]. Technological Forecasting and Social Change, 2020, 154: 119961. 本文引用 [1]

[46]	SKJÆRSETH J B, WETTESTAD J. EU emissions trading: initiation, decision-making and implementation[M]. Routledge, 2016. 本文引用 [1]

[47]

中华人民共和国生态环境部. 碳排放权交易管理办法(第19号令) [EB/OL].(2021-02-01)[2024-06-10]. http://www.gov.cn/gongbao/content/2021/content_5591410.htm.

http://www.gov.cn/gongbao/content/2021/content_5591410.htm

Ministry of Ecology and Environment of the People's Republic of China. Regulation on the management of carbon emission trading rights (Order No.19)[EB/OL]. (2021-02-01)[2024-06-10]. http://www.gov.cn/gongbao/content/2021/content_5591410.htm.

http://www.gov.cn/gongbao/content/2021/content_5591410.htm

本文引用 [1]

[48]	HU Y J, YANG L S, DUAN F L, et al. A scientometric analysis and review of the emissions trading system[J]. Energies, 2022, 15(12): 4423. 本文引用 [1]

[49]	Gagelmann F. The influence of the allocation method on market liquidity, volatility and firms’ investment decisions[M]. Emissions Trading:Institutional Design, Decision Making and Corporate Strategies, 2008: 69-88. 本文引用 [1]

[50]	宣晓伟, 张浩. 碳排放权配额分配的国际经验及启示[J]. 中国人口·资源与环境, 2013, 23(12): 10-15. XUAN Xiaowei, ZHANG Hao. International experiences and lessons of carbon emission permit allocation method[J]. China Population, Resources and Environment, 2013, 23(12): 10-15. 本文引用 [1]

[51]

杨军, 赵永斌, 丛建辉. 全国统一碳市场碳配额的总量设定与分配: 基于碳交易三大特性的再审视[J]. 天津社会科学, 2017(5): 110-114.

YANG

Jun

, ZHAO

Yongbin

, CONG

Jianhui

. The setting and allocation of the total carbon quota in the national unified carbon market: re-examination based on the three characteristics of carbon trading[J]. Tianjin Social Sciences, 2017(5): 110-114.

本文引用 [1]

[52]

刘国中, 文福拴, 薛禹胜. 温室气体排放权交易对发电公司最优报价策略的影响[J]. 电力系统自动化, 2009, 33(19): 15-20.

LIU

Guozhong

, WEN

Fushuan

, XUE

Yusheng

. Impacts of emissions trading on optimal bidding strategies of generation companies in day-ahead electricity markets[J]. Automation of Electric Power Systems, 2009, 33(19): 15-20.

本文引用 [1]

[53]	MORCILLO J D, FRANCO C J, ANGULO F. Simulation of demand growth scenarios in the Colombian electricity market: an integration of system dynamics and dynamic systems[J]. Applied Energy, 2018, 216: 504-520. 本文引用 [1]

[54]	KONTOCHRISTOPOULOS Y, MICHAS S, KLEANTHIS N, et al. Investigating the market effects of increased RES penetration with BSAM: a wholesale electricity market simulator[J]. Energy Reports, 2021, 7: 4905-4929. 本文引用 [1]

[55]	柴雪, 苏子航, 李建男, 等. 面向现货市场仿真的发电商有限理性智能体报价模型[J]. 电网技术, 2022, 46(12): 4800-4808. CHAI Xue, SU Zihang, LI Jiannan, et al. Bounded rational agent bidding model of generators for spot market simulation[J]. Power System Technology, 2022, 46(12): 4800-4808. 本文引用 [1]

[56]

宋怡, 林晨韵, 梁高琪, 等. 基于电力现货市场仿真的海上风电接入对广东省电力行业碳减排影响评估[J]. 全球能源互联网, 2020, 3(4): 363-373.

SONG

, LIN

Chenyun

, LIANG

Gaoqi

, et al. Assessing the impacts of large-scale offshore wind power integration on carbon emission reduction in Guangdong Province based on electricity spot market simulation[J]. Journal of Global Energy Interconnection, 2020, 3(4): 363-373.

本文引用 [1]

[57]	林楚. 建设我国新型电力系统将分“三步走”[N]. 机电商报,2023-01-16(A06) LIN Chu. Construction of China’s new-type power system to proceed in ‘three steps’[N]. Mechanical and Electrical Business News, 2023-01-16( A06). 本文引用 [1]

[58]	ZHANG R F, JIANG T, LI F X, et al. Bi-level strategic bidding model for P2G facilities considering a carbon emission trading scheme-embedded LMP and wind power uncertainty[J]. International Journal of Electrical Power & Energy Systems, 2021, 128: 106740. 本文引用 [1]

[59]

卢治霖, 刘明波, 尚楠, 等. 考虑碳排放权交易市场影响的日前电力市场两阶段出清模型[J]. 电力系统自动化, 2022, 46(10): 159-170.

Zhilin

, LIU

Mingbo

, SHANG

Nan

, et al. Two-stage clearing model for day-ahead electricity market considering impact of carbon emissions trading market[J]. Automation of Electric Power Systems, 2022, 46(10): 159-170.

本文引用 [1]

[60]	RINGLER P. PowerACE agent-based simulation of electricity markets[C]// InMOCAP Workshop on Modelling Carbon Prices-Interacting Agent Networks & Strategies Under Risk, 2012. 本文引用 [1]

[61]	RUHNAU O, BUCKSTEEG M, RITTER D, et al. Why electricity market models yield different results: Carbon pricing in a model-comparison experiment[J]. Renewable and Sustainable Energy Reviews, 2022, 153: 111701. 本文引用 [1]

[62]	CONG R G, WEI Y M. Potential impact of (CET) carbon emissions trading on China’s power sector: a perspective from different allowance allocation options[J]. Energy, 2010, 35(9): 3921-3931. 本文引用 [2]

[63]	王一, 吴洁璇, 王浩浩, 等. 碳排放权市场与中长期电力市场交互作用影响分析[J]. 电力系统及其自动化学报, 2020, 32(10): 44-54. WANG Yi, WU Jiexuan, WANG Haohao, et al. Analysis of interactions between carbon emission trading market and medium-and long-term electricity market[J]. Proceedings of the CSU-EPSA, 2020, 32(10): 44-54. 本文引用 [1]

[64]	赵长红, 张明明, 吴建军, 等. 碳市场和电力市场耦合研究[J]. 中国环境管理, 2019, 11(4): 105-112. ZHAO Changhong, ZHANG Mingming, WU Jianjun, et al. The coupling study on carbon market and power market[J]. Chinese Journal of Environmental Management, 2019, 11(4): 105-112. 本文引用 [1]

[65]	朱丽洁. 中国碳交易价格与电力价格相关性研究[J]. 中国林业经济, 2021(2): 52-55. ZHU Lijie. Research on the correlation between China’s carbon trading price and electricity price[J]. China Forestry Economics, 2021(2): 52-55. 本文引用 [1]

[66]	曹一家. 并行遗传算法在电力系统经济调度中的应用: 迁移策略对算法性能的影响[J]. 电力系统自动化, 2002, 26(13): 20-24. CAO Yijia. Application of parallel genetic algorithms to economic dispatch : effects of migration strategy on algorithms’ performances[J]. Automation of Electric Power Systems, 2002, 26(13): 20-24. 本文引用 [1]

[67]	ZAKARIA A, ISMAIL F B, HOSSAIN LIPU M S, et al. Uncertainty models for stochastic optimization in renewable energy applications[J]. Renewable Energy, 2020, 145: 1543-1571. 本文引用 [1]

[68]	刘晓雄, 蔺红. 基于模型预测控制的源荷储低碳经济调度[J]. 电测与仪表, 2024, 61(7): 153-160. LIU Xiaoxiong, LIN Hong. Low-carbon economic dispatching of source, load and storage based on model predictive control[J]. Electrical Measurement & Instrumentation, 2024, 61(7): 153-160. 本文引用 [1]

[69]	陈海焱, 陈金富, 段献忠. 含风电场电力系统经济调度的模糊建模及优化算法[J]. 电力系统自动化, 2006, 30(2): 22-26. CHEN Haiyan, CHEN Jinfu, DUAN Xianzhong. Fuzzy modeling and optimization algorithm on dynamic economic dispatch in wind power integrated system[J]. Automation of Electric Power Systems, 2006, 30(2): 22-26. 本文引用 [1]

[70]	ANTONIADOU-PLYTARIA K, STEEN D, TUAN L A, et al. Scenario-based stochastic optimization for energy and flexibility dispatch of a microgrid[J]. IEEE Transactions on Smart Grid, 2022, 13(5): 3328-3341. 本文引用 [1]

[71]	PATURET M, MARKOVIC U, DELIKARAOGLOU S, et al. Stochastic unit commitment in low-inertia grids[J]. IEEE Transactions on Power Systems, 2020, 35(5): 3448-3458. 本文引用 [1]

[72]	刘亚. 面向惯量和调频备用需求的电力系统优化调度方法[D]. 上海: 上海电力大学, 2021. LIU Ya. Optimal dispatching method of power system for inertia and frequency modulation reserve demand[D]. Shanghai: Shanghai University of Electric Power, 2021. 本文引用 [1]

[73]	TENG F, TROVATO V, STRBAC G. Stochastic scheduling with inertia-dependent fast frequency response requirements[J]. IEEE Transactions on Power Systems, 2016, 31(2): 1557-1566. 本文引用 [1]

[74]	陈启鑫, 康重庆, 夏清, 等. 低碳电力调度方式及其决策模型[J]. 电力系统自动化, 2010, 34(12): 18-23. CHEN Qixin, KANG Chongqing, XIA Qing, et al. Mechanism and modelling approach to low-carbon power dispatch[J]. Automation of Electric Power Systems, 2010, 34(12): 18-23. 本文引用 [1]

[75]	LIU G, QIN Z F, DIAO T Y, et al. Low carbon economic dispatch of biogas-wind-solar renewable energy system based on robust stochastic optimization[J]. International Journal of Electrical Power & Energy Systems, 2022, 139: 108069. 本文引用 [1]

[76]	XIANG Y, WU G, SHEN X D, et al. Low-carbon economic dispatch of electricity-gas systems[J]. Energy, 2021, 226: 120267. 本文引用 [1]

[77]

王贵斌, 赵俊华, 文福拴, 等. 配电系统中电动汽车与可再生能源的随机协同调度[J]. 电力系统自动化, 2012, 36(19): 22-29.

WANG

Guibin

, ZHAO

Junhua

, WEN

Fushuan

, et al. Stochastic optimization dispatching of plug-in hybrid electric vehicles in coordination with renewable generation in distribution systems[J]. Automation of Electric Power Systems, 2012, 36(19): 22-29.

本文引用 [1]

[78]	MÜHLPFORDT T, ROALD L, HAGENMEYER V, et al. Chance-constrained AC optimal power flow: a polynomial chaos approach[J]. IEEE Transactions on Power Systems, 2019, 34(6): 4806-4816. 本文引用 [1]

[79]	YANG J, SU C Q. Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty[J]. Energy, 2021, 223: 120043. 本文引用 [1]

[80]	HUANG W J, ZHENG W Y, HILL D J. Distributionally robust optimal power flow in multi-microgrids with decomposition and guaranteed convergence[J]. IEEE Transactions on Smart Grid, 2021, 12(1): 43-55. 本文引用 [1]

[81]	JABR R A. Distributionally robust CVaR constraints for power flow optimization[J]. IEEE Transactions on Power Systems, 2020, 35(5): 3764-3773. 本文引用 [1]

[82]	KHAN I U, JAVAID N, GAMAGE K A A, et al. Heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources[J]. IEEE Access, 2020, 8: 148622-148643. 本文引用 [1]

[83]	YAN Z M, XU Y. Real-time optimal power flow: a Lagrangian based deep reinforcement learning approach[J]. IEEE Transactions on Power Systems, 2020, 35(4): 3270-3273. 本文引用 [1]

[84]	AKBARI-DIBAVAR A, MOHAMMADI-IVATLOO B, ZARE K. Electricity market pricing:uniform pricing vs. pay-as-bid pricing[M]// Electricity Markets. Cham: Springer International Publishing, 2020: 19-35. 本文引用 [1]

[85]	XIONG G, OKUMA S, FUJITA H. Multi-agent based experiments on uniform price and pay-as-bid electricity auction markets[C]// 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. IEEE, 2004: 72-76. 本文引用 [1]

[86]	SON Y S, BALDICK R, LEE K H, et al. Short-term electricity market auction game analysis: uniform and pay-as-bid pricing[J]. IEEE Transactions on Power Systems, 2004, 19(4): 1990-1998. 本文引用 [1]

[87]	FEDERICO G, RAHMAN D M. Bidding in an electricity pay-as-bid auction[J]. Journal of Regulatory Economics, 2003, 24(2): 175-211. 本文引用 [1]

[88]	ALIABADI D E, KAYA M, GÜVENÇ Ş. An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms[J]. Energy Policy, 2017, 100: 191-205. 本文引用 [1]

[89]	李晓刚, 言茂松, 谢贤亚. 3种定价方法对发电厂商报价策略的诱导机理[J]. 电力系统自动化, 2003, 27(5): 20-25. LI Xiaogang, YAN Maosong, XIE Xianya. Inducement mechanism of strategic bidding under three typical pricing methods[J]. Automation of Electric Power Systems, 2003, 27(5): 20-25. 本文引用 [1]

[90]

唐成鹏, 张粒子, 刘方, 等. 基于多智能体强化学习的电力现货市场定价机制研究(一): 不同定价机制下发电商报价双层优化模型[J]. 中国电机工程学报, 2021, 41(2): 536-553.

TANG

Chengpeng

, ZHANG

Lizi

, LIU

Fang

, et al. Research on pricing mechanism of electricity spot market based on multi-agent reinforcement learning(part I): bi-level optimization model for generators under different pricing mechanisms[J]. Proceedings of the CSEE, 2021, 41(2): 536-553.

本文引用 [1]

[91]	KEELEY A R, MATSUMOTO K, TANAKA K, et al. The impact of renewable energy generation on the spot market price in Germany: ex-post analysis using boosting method[J]. The Energy Journal, 2020, 41(suppl_1): 119-140. 本文引用 [1]

[92]	RÍOS-OCAMPO J P, ARANGO-ARAMBURO S, LARSEN E R. Renewable energy penetration and energy security in electricity markets[J]. International Journal of Energy Research, 2021, 45(12): 17767-17783. 本文引用 [1]

[93]	孟繁林, 钟海旺, 夏清. 基于非凸报价的高比例新能源现货市场机制[J]. 电网技术, 2023, 47(1): 120-128. MENG Fanlin, ZHONG Haiwang, XIA Qing. Non-convex bidding-based spot market mechanism of high penetration renewable energy[J]. Power System Technology, 2023, 47(1): 120-128. 本文引用 [1]

[94]	胡荷娟, 孙晓燕, 曾博, 等. 考虑源-荷不确定性的矿山综合能源系统多时间尺度区间优化调度[J]. 控制与决策, 2024, 39(3): 827-835. HU Hejuan, SUN Xiaoyan, ZENG Bo, et al. Multi-time-scale interval optimal dispatch of coal mine integrated energy system considering source-load uncertainty[J]. Control and Decision, 2024, 39(3): 827-835. 本文引用 [1]

[95]

陈图南, 李文萱, 李云, 等. “双碳” 背景下碳-绿证-电力市场耦合机制综述[J]. 广东电力, 2024, 37(8): 14-25.

CHEN

Tunan

, LI

Wenxuan

, LI

Yun

, et al. Review on coupling mechanism of carbon, green certificate and power market under the background of carbon peaking and carbon neutrality[J]. Guangdong Electric Power, 2024, 37(8): 14-25.

本文引用 [1]

[96]

钟立华, 潘峰, 杨雨瑶, 等. 碳计量视角下绿色电力交易对碳市场主体行为决策的影响机制研究[J]. 电测与仪表, 2025, 62(1): 68-79.

ZHONG

Lihua

, PAN

Feng

, YANG

Yuyao

, et al. A study on the impact mechanism of green electricity trading on the decision-making behavior of carbon market participants from the perspective of carbon measurement[J]. Electrical Measurement & Instrumentation, 2025, 62(1): 68-79.

本文引用 [1]

[97]	PHAM Q V, RUBY R, FANG F, et al. Aerial computing: a new computing paradigm, applications, and challenges[J]. IEEE Internet of Things Journal, 2022, 9(11): 8339-8363. 本文引用 [1]

[98]	JI C J, HU Y J, TANG B J. Research on carbon market price mechanism and influencing factors: a literature review[J]. Natural Hazards, 2018, 92(2): 761-782. 本文引用 [1]

[99]	SONG Y Z, LIU T S, YE B, et al. Linking carbon market and electricity market for promoting the grid parity of photovoltaic electricity in China[J]. Energy, 2020, 211: 118924. 本文引用 [1]

[100]

ZHANG

L R

, LI

Y K

, JIA

Z J

. Impact of carbon allowance allocation on power industry in China’s carbon trading market: computable general equilibrium based analysis[J]. Applied Energy, 2018, 229: 814-827.

本文引用 [1]