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

ZHAO Junhua; BAI Yan; WANG Zhidong

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Electric Power Construction ›› 2025

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 Yan¹, WANG Zhidong³

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Abstract

[Objective] The development of the new power system has paved the way for promoting the low-carbon transition of China's power grid. 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 system pivotal for addressing low-carbon dispatch challenges. [Methods] This paper, from the perspective of electro-carbon coupling, clarifies the interactive impact between the electricity market and the carbon market. It investigates low-carbon operational strategies and market mechanism designs within the 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 five key technologies for low-carbon dispatch along with their research limitations. [Results] The findings reveal that existing research exhibits deficiencies in the aforementioned dimensions. In particular, during the integration of electricity and carbon markets, unclear coupling mechanisms and the absence of an effective quota allocation mechanism render the market coordination process static and overly simplified. Moreover, market simulation methods confront a contradiction between insufficient interpretability and overly stringent assumptions, while the integration of renewable energy units (characterized by near-zero short-term marginal costs) undermines traditional pricing models and complicates multi-period cost allocation. [Conclusions] To address these challenges, this paper 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.

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energy structure / energy management / new power system / low-carbon transition / low-carbon operation and scheduling

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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

References

[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(06):627-628.
ZHOU Taidong, WANG Luo, SHI Xunpeng.Clean Energy Transition and Global Development Pathways[J]. Journal of Global Energy Interconnection, 2024, 7(06): 627-628.
[2] 习近平. 在第七十五届联合国大会一般性辩论上的讲话[R].北京:中华人民共和国国务院,2020.
XI Jinping.Speech at the general debate of the 75th session of the united nations general assembly[R]. Beijing: State Council of the People's Republic of China, 2020(in Chinese).
[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 and Accounting, 2021, 4: 4-5.
[4] 国家能源局.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].http://www.nea.gov.cn/2023-01/06/c_1310688702.htm.
National Energy Administration. 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]. http://www.nea.gov.cn/2023-01/06/c_1310688702.htm.
[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.
[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(04):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(04): 83-91.
[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(08):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(08): 2806-2819.
[8] 权威数据. 2022年二季度全国新能源电力消纳评估分析[EB/OL]. https://news.bjx.com.cn/html/20220907/1253622.shtml
Authority Data. National New Energy Power Consumption Assessment and Analysis for the Second Quarter of2022 [EB/OL]. https://news.bjx.com.cn/html/20220907/1253622.shtml
[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(06):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 Hydropower Engineering, 2023, 42(06): 23-29.
[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.
[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(05):113-125.
LI Xiangguang, TAN Qingbo, LI Fanqi, et al.Analysis model of the impact of electricity-carbon coupling on settlement prices in the spot market for coal power units[J]. Electric Power, 2024, 57(05): 113-125 (in Chinese).
[12] R. Nassar, T. G. Hill, C. A.McLinden, D. Wunch, D. B. Jones, and D. Crisp, “Quantifying CO2 emissions from individual power plants from space,” Geophysical Research Letters, vol. 44, no. 19, pp. 10045-10053, 2017.
[13] B. Zheng, F. Chevallier, P. Ciais, et al.Observing carbon dioxide emissions over China's cities and industrial areas with the Orbiting Carbon Observatory-2[J]. Atmospheric Chemistry and Physics, 20(14): 8501-8510, 2020.
[14] J. T. Shaw, A. Shah, H. Yong, et al. Methods for quantifying methane emissions using unmanned aerial vehicles: a review[J]. Philosophical Transactions of the Royal Society A, 379(2210): 20200450, 2021.
[15] J. Salas-Navarro, J. Stix, J. M. de Moor. A new Multi-GAS system for continuous monitoring of CO2/CH4 ratios at active volcanoes[J]. Journal of Volcanology and Geothermal Research, 426: 107533, 2022.
[16] M. Reuter, M. Buchwitz, H. Bovensmann, et al.UAV based measurements of CO2 emissions from anthropogenic point sources[J]. EGU General Assembly Conference Abstracts, 1641, 2020.
[17] C. Frankenberg, R. Pollock, R. A. M.Lee, et al. The Orbiting Carbon Observatory (OCO-2): spectrometer performance evaluation using pre-launch direct sun measurements[J]. Atmospheric Measurement Techniques, 8(1): 301-313, 2015.
[18] J. P.Ríos-Ocampo, S. Arango-Aramburo, E. R. Larsen, Renewable energy penetration and energy security in electricity market[J]. International Journal of Energy Research, 45(12): 17767-17783, 2021.
[19] L. Ji, S. Liang, S. Qu, et al.Greenhouse gas emission factors of purchased electricity from interconnected grids[J]. Applied Energy, 184: 751-758, 2016.
[20] G. Liu, J. Liu, J. Zhao, et al.Real-Time Corporate Carbon Footprint Estimation Methodology Based on Appliance Identification[J]. IEEE Transactions on Industrial Informatics, 19(2): 1401-1412, 2022.
[21] C. Kang, T. Zhou, Q. Chen, et al.Carbon emission flow from generation to demand: A network-based model[J]. IEEE Transactions on Smart Grid, 6(5): 2386-2394, 2015.
[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.
[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(07):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(07): 84-91.
[24] 程祥,李林芝,吴浩,丁一,宋永华,孙维真.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.
[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(01):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]. Research on Environmental Economics, 2021, 6(01): 77-92.
[26] D. Pandey, M. Agrawal, J. S. Pandey.Carbon footprint: current methods of estimation[J]. Environmental Monitoring and Assessment, 178: 135-160, 2011.
[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.
[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(04):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(04): 40-48.
[29] S. Hoffmann, W. Lasarov, H. Reimers.Carbon footprint tracking apps. What drives consumers' adoption intention[J]. Technology in Society, 69: 101956, 2022.
[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(07):71-78.
Wang Wei, Lin Jianyi, Cui Shenghui, et al.An overview of carbon footprint analysis[J]. Environmental Science and Technology, 2010, 33(07): 71-78.
[31] L. Guzman, S. Makonin, A. Clapp.CarbonKit: Designing a personal carbon tracking platform[J]. Proceedings of the Fourth International Workshop on Social Sensing, 24-29, 2019.
[32] C. Dwork. Differential privacy[C]. Automata, Languages and Programming: 33rd International Colloquium, ICALP2006, Venice, Italy, July 10-14, 2006, Proceedings, Part II 33, 4052: 1-12, 2006.
[33] S. Willcox, C. Meinig, C. L. Sabine, et al.An autonomous mobile platform for underway surface carbon measurements in open-ocean and coastal waters[C]. OCEANS 2009, 1-8, 2009.
[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(01):246-258.
Feng Dengguo, Zhang Min, Li Hao.Big data security and privacy protection[J]. Chinese Journal of Computers, 2014, 37(01): 246-258.
[35] H. Hui, C. Zhou, S. Xu, et al.A novel secure data transmission scheme in industrial internet of things[J]. China Communications, 17(1): 73-88, 2020.
[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(07):15-17+20.
Zhang Lili, Zhang Yuqing. Brute force cracking of RC4 encryption algorithm based on distributed computing[J]. Computer Engineering and Science, 2008(07): 15-17+20.
[37] B. McMahan, E. Moore, D. Ramage, et al.Communication-efficient learning of deep networks from decentralized data[J]. Artificial intelligence and statistics, 54: 1273-1282, 2017.
[38] H. Pötter, S. Lee, D. Mossé.Towards privacy-preserving framework for non-intrusive load monitoring[J]. Proceedings of the Twelfth ACM international conference on future energy systems, 259-263, 2021.
[39] D. I. Dimitrov, M. Balunovic, N. Konstantinov, et al.Data leakage in federated averaging[J]. Transactions on Machine Learning Research, 1-24, 2022.
[40] K. Wei, J. Li, M. Ding, et al.Federated learning with differential privacy: Algorithms and performance analysis[J]. IEEE Transactions on Information Forensics and Security, 15: 3454-3469, 2020.
[41] Y. Aono, T. Hayashi, L. Wang, et al.Privacy-preserving deep learning via additively homomorphic encryption[J]. IEEE Transactions on Information Forensics and Security, 13(5): 1333-1345, 2017.
[42] Y. Li, T. Feng, L. Liu, et al.How do the electricity market and carbon market interact and achieve integrated development? A bibliometric-based review[J]. Energy, 265: 126308.
[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]. People's Forum: Academic Frontier, 2022(13): 56-65.
[44] Y. Gao, M. Li, J. Xue, et al.Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation[J]. Energy Economic, 90: 104872, 2020.
[45] X. Zhang, D. Gan, Y. Wang, 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, 154: 119961, 2020.
[46] Skjærseth J B, Wettestad J.EU emissions trading: initiation, decision-making and implementation[M]. Routledge, 2016.
[47] 中华人民共和国生态环境部令(第19号)碳排放权交易管理办法[EB/OL].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]. Available from: http://www.gov.cn/gongbao/content/2021/content_5591410.htm
[48] Y. Hu, L. Yang, F. Duan, et al.A Scientometric Analysis and Review of the Emissions Trading System[J]. Energies, 15(12): 4423, 2022.
[49] F. Gagelmann.The influence of the allocation method on market liquidity, volatility and firms' investment decisions[M]. Emissions Trading: Institutional Design, Decision Making and Corporate Strategies, 69-88, 2008.
[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.
[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, 216(05):110-114.
Yang Jun, Zhao Yongbin, Guo Jianhui.Total quantity setting and allocation of carbon quotas in the national unified carbon market: A re-examination based on the three major characteristics of carbon trading[J]. Tianjin Social Sciences, 2017, 216(05): 110-114.
[52] 刘国中,文福栓,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): 5-10.
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): 5-10.
[53] J.D. Morcillo, C.J. Franco, F. Angulo, et al.Simulation of demand growth scenarios in the Colombian electricity market: An integration of system dynamics and dynamic systems[J]. Applied Energy, 216: 504-520, 2018.
[54] Y. Kntochristopoulos, S. Michas, N. Kleanthis, et al.Investigating the market effects of increased RES penetration with BSAM: A wholesale electricity market simulator[J]. Energy Reports, 7: 4905-4929, 2021.
[55] 柴雪,苏子航,李建男,张娜,吕泉.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):4800-4810.
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): 4800-4810.
[56] 宋怡,林晨韵,梁高琪,赵俊华.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(04):363-373.
Song Yi, 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]. Global Energy Interconnection, 2020, 3(04): 363-373.
[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).
[58] R. Zhang, T. Jiang, F. Li, 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, 128: 106740, 2021.
[59] 卢治霖,刘明波,尚楠,陈政,张妍,黄国日.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.
Lu Zhilin, Liu Mingbo, Shang Nan, et al.Two-stage clearing model for day-ahead electricity market considering the impact of carbon emissions trading market[J]. Automation of Electric Power Systems, 2022, 46(10): 159-170.
[60] P. Ringler.PowerACE Agent-based simulation of electricity markets[C]. InMOCAP Workshop on Modelling Carbon Prices-Interacting agent networks & Strategies under risk, 2012.
[61] O. Ruhnau, M. Bucksteeg, D. Ritter, et al.Why electricity market models yield different results: Carbon pricing in a model-comparison experiment[J]. Renewable and Sustainable Energy Reviews, 153: 111701, 2022
[62] R. Cong, Y. Wei.Potential impact of carbon emissions trading (CET) on China's power sector: A perspective from different allowance allocation options[J]. Energy, 35(9): 3921-3931, 2010.
[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 the carbon emission trading market and medium-long term electricity market[J]. Journal of Power System and Automation, 2020, 32(10): 44-54.
[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(04):105-112.
Zhao Changhong, Zhang Mingming, Wu Jianjun, et al.Study on the coupling of carbon market and electricity market[J]. China Environmental Management, 2019, 11(04): 105-112.
[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(02):52-55.
Zhu Lijie.Research on the correlation between China's carbon trading prices and electricity prices[J]. China Forestry Economics, 2021(02): 52-55.
[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(13):20-24.
Cao Yijia.Application of parallel genetic algorithm of economic dispatch to power systems—Effects of migration strategy on algorithm performance[J]. Automation of Electric Power Systems, 2002(13): 20-24.
[67] A. Zakaria, F. B. Ismail, M. S. H.Lipu, et al. Uncertainty models for stochastic optimization in renewable energy applications[J]. Renewable Energy, 145: 1543-1571, 2020.
[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(07):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(07): 153-160.
[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):5.
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): 5.
[70] K. Antoniadou-Plytaria, D. Steen, L. A. Tuan, et al.Scenario-based stochastic optimization for energy and flexibility dispatch of a microgrid[J]. IEEE Transactions on Smart Grid, 13(5): 3328-3341, 2022.
[71] M. Paturet, U. Markovic, S. Delikaraoglou, et al.Stochastic unit commitment in low-inertia grids[J]. IEEE Transactions on Power Systems, 35(5): 3448-3458, 2020.
[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].上海电力大学,2021.
Liu Ya.Power system optimal dispatch method for inertia and frequency response reserve demand [D]. Shanghai University of Electric Power, 2021.
[73] F. Teng, V. Trovato, G. Strbac.Stochastic scheduling with inertia-dependent fast frequency response requirements[J]. IEEE Transactions on Power Systems, 31(2): 1557-1566, 2016.
[74] 陈启鑫,康重庆,夏清,Daniel KIRSCHEN.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.Low-carbon power dispatch methods and their decision models[J]. Automation of Electric Power Systems, 2010, 34(12): 18-23.
[75] G. Liu, Z. Qin, T. Diao, 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, 139: 108069.
[76] Y. Xiang, G. Wu, X. Shen, et al.Low-carbon economic dispatch of electricity-gas systems[J]. Energy, 226: 120267, 2021.
[77] 王贵斌,赵俊华,文福拴,薛禹胜,辛建波.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 energy in distribution systems[J]. Automation of Electric Power Systems, 2012, 36(19): 22-29.
[78] T. Mühlpfordt, L. Roald, V. Hagenmeyer, et al.Chance-constrained AC optimal power flow: a polynomial chaos approach[J]. IEEE Transactions on Power Systems, 34(6): 4806-4816, 2019.
[79] J. Yang, C. Su.Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty[J]. Energy, 223: 120043, 2021.
[80] W. Huang, W. Zheng, D. J. Hill, et al.Distributionally robust optimal power flow in multi-microgrids with decomposition and guaranteed convergence[J]. IEEE Transactions on Smart Grid, 12(1): 43-55, 2020.
[81] R. A. Jabr.Distributionally robust CVaR constraints for power flow optimization[J]. IEEE Transactions on Power Systems, 35(5): 3764-3773, 2020.
[82] I. U. Khan, N. Javaid, K. A. A.Gamage, et al. Heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources[J]. IEEE Access, 8: 148622-148643, 2020.
[83] Z. Yan, Y. Xu.Real-time optimal power flow: a lagrangian based deep reinforcement learning approach[J]. IEEE Transactions on Power Systems, 35(4): 3270-3273, 2020.
[84] A. Akbari-Dibavar, B. Mohammadi-Ivatloo, K. Zare.Electricity market pricing: uniform pricing vs. pay-as-bid pricing.Electricity Markets: New Players and Pricing Uncertainties, 19-35, 2020.
[85] G. Xiong, S. Okuma, H. Fujita. Multi-agent based experiments on uniform price and pay-as-bid electricity auction markets.2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings, 1: 72-76, 2004.
[86] Y. S. Son, R. Baldick, K. H. Lee, et al.Short-term electricity market auction game analysis: uniform and pay-as-bid pricing[J]. IEEE Transactions on Power Systems, 19(4): 1990-1998, 2004.
[87] G. Federico, D. Rahman.Bidding in an electricity pay-as-bid auction[J]. Journal of Regulatory Economics, 24(2): 175-211, 2003.
[88] D. E. Aliabadi, M. Kaya, G. Şahin.An agent-based simulation of power generation company behavior in electricity markets under different market-clearing mechanisms[J]. Energy Policy, 100: 191-205, 2017.
[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(05):20-25.
Li Xiaogang, Yan Maosong, Xie Xianya.The inducement mechanism of three pricing methods on power plant bidding strategies[J]. Automation of Electric Power Systems, 2003(05): 20-25.
[90] 唐成鹏,张粒子,刘方,李雲建.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(02):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 Chinese Society for Electrical Engineering, 2021, 41(02): 536-553.
[91] A. R. Keeley, K. I. Matsumoto, K. Tanaka, 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, 41: 1-45, 2020.
[92] R. J.Píos-Ocampo, S. Arango-Aramburo, E. R. Larsen. Renewable energy penetration and energy security in electricity markets[J]. International Journal of Energy Research, 45(12): 17767-17783, 2021.
[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(01):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(01): 120-128.
[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.
[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(08):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(08): 14-25.
[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(01):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(01): 68-79.
[97] Q. V. Pham, R. Ruby, F. Fang, et al.Aerial computing: a new computing paradigm, applications, and challenges[J]. IEEE Internet of Things Journal, 9(11): 8339-8363, 2022.
[98] C. Ji, Y. Hu, B. Tang.Research on carbon market price mechanism and influencing factors: a literature review[J]. Natural Hazards, 92: 761-782, 2018.
[99] Y. Song, T. Liu, B. Ye, et al.Linking carbon market and electricity market for promoting the grid parity of photovoltaic electricity in China[J]. Energy, 211: 118924, 2020.
[100] L. Zhang, Y. Li, Z. Jia.Impact of carbon allowance allocation on power industry in China's carbon trading market: computable general equilibrium based analysis[J]. Applied Energy, 229: 814-827, 2018.