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1.华北电力大学电气与电子工程学院,北京市 102206
2.国网浙江省电力有限公司电力科学研究院,浙江省杭州市 310014
3.国网浙江省电力有限公司电力市场仿真实验室,浙江省杭州市 310014
4.国网浙江省电力有限公司,浙江省杭州市 310000
Received:10 October 2021,
Revised:2022-02-10,
Published Online:02 April 2022,
Published:25 May 2022
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唐成鹏,张粒子,邓晖等.考虑风险管理的电力市场多时段均衡分析方法[J].电力系统自动化,2022,46(10):171-180.
TANG Chengpeng,ZHANG Lizi,DENG Hui,et al.Multi-period Equilibrium Analysis Method for Electricity Market Considering Risk Management[J].Automation of Electric Power Systems,2022,46(10):171-180.
唐成鹏,张粒子,邓晖等.考虑风险管理的电力市场多时段均衡分析方法[J].电力系统自动化,2022,46(10):171-180. DOI: 10.7500/AEPS20211010004.
TANG Chengpeng,ZHANG Lizi,DENG Hui,et al.Multi-period Equilibrium Analysis Method for Electricity Market Considering Risk Management[J].Automation of Electric Power Systems,2022,46(10):171-180. DOI: 10.7500/AEPS20211010004.
均衡分析方法是电力市场运行效率分析及机制设计论证的有力工具,而如何计及差价合同和市场主体风险偏好的影响,以及高效求解多时段均衡模型,已成为使电力市场均衡分析方法实用化亟待解决的问题。从差价合同的确定、考虑风险偏好的电力市场均衡建模、基于多智能体深度强化学习的求解等方面,提出了考虑风险管理的电力市场多时段均衡分析方法。在模型框架方面,分别针对市场化差价合同和政府授权差价合同,提出了基于市场均衡结果合理确定合同价格及其曲线的方法;采用条件风险价值评估市场风险,并建立了发电商报价决策的随机优化模型;结合前瞻性安全约束机组组合和经济调度模型建立了现货市场出清模型,以保证结果的合理性。在求解算法方面,通过改进深度强化学习方法,提出了基于风险管理的多智能体深度强化学习算法,并对模型进行迭代求解。最后,通过算例验证了均衡分析方法的合理性和有效性,并剖析了不同比例市场化差价合同或政府授权差价合同,以及不同风险偏好对市场均衡的影响。
An equilibrium analysis method is a powerful tool for the operation efficiency analysis as well as mechanical design and demonstration of electricity market. However
how to consider the influence of contracts for differences (CFDs) and the risk preference of market players
and how to solve the multi-period equilibrium model efficiently have become urgent problems to be solved in the practical application of the equilibrium analysis method for electricity market. In this paper
a multi-period equilibrium analysis method for electricity market considering the risk management is put forward from the aspects of the determination of CFDs
the equilibrium modeling of the electricity market considering risk preference
and the model solving based on the multi-agent deep reinforcement learning. In terms of the model framework
the methods for determining the contract price and curve reasonably based on the market equilibrium results are proposed for market-based CFDs and government-authorized CFDs
respectively; by using conditional value-at-risk to measure market risk
the stochastic optimization models for the offer decisions of generators are established; and the spot market clearing model is established by combining forward-looking security-constrained unit commitment (SCUC) and security-constrained economic dispatch (SCED) models to ensure the rationality of the results. For the solving algorithm
with the improvement of the deep reinforcement learning method
a risk-managing multi-agent deep reinforcement learning algorithm is proposed to solve the model iteratively. Finally
the numerical examples verify the rationality and effectiveness of the equilibrium analysis method
and the impact of different ratios of market-based CFDs or government-authorized CFDs
and different risk preferences on market equilibrium are analyzed.
张粒子 , 唐成鹏 , 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(二):结合理论与仿真的定价机制决策框架 [J]. 中国电机工程学报 , 2021 , 41 ( 3 ): 1004 - 1018 .
ZHANG Lizi , TANG Chengpeng , LIU Fang , et al . Research on pricing mechanism of electricity spot market based on multi-agent reinforcement learning(Part Ⅱ): decision-making framework of pricing mechanism combined with theory and simulation [J]. Proceedings of the CSEE , 2021 , 41 ( 3 ): 1004 - 1018 .
ZHANG X P . Restructured electric power systems: analysis of electricity markets with equilibrium models [M]. New Jersey, USA : Wiley-IEEE Press , 2010 : 99 - 137 .
HASSAN A , DVORKIN Y . Energy storage siting and sizing in coordinated distribution and transmission systems [J]. IEEE Transactions on Sustainable Energy , 2018 , 9 ( 4 ): 1692 - 1701 .
RUIZ C , CONEJO A J . Pool strategy of a producer with endogenous formation of locational marginal prices [J]. IEEE Transactions on Power Systems , 2009 , 24 ( 4 ): 1855 - 1866 .
舒畅 , 钟海旺 , 夏清 . 基于优化理论市场化的日前电力市场机制设计 [J]. 电力系统自动化 , 2016 , 40 ( 2 ): 55 - 62 .
SHU Chang , ZHONG Haiwang , XIA Qing . Day-ahead electricity market design based on market interpretation of optimization theory [J]. Automation of Electric Power Systems , 2016 , 40 ( 2 ): 55 - 62 .
ZOU P , CHEN Q X , XIA Q , et al . Pool equilibria including strategic storage [J]. Applied Energy , 2016 , 177 : 260 - 270 .
张妍 , 陈启鑫 , 郭鸿业 , 等 . 引入投资决策的电力容量市场均衡分析 [J]. 电力系统自动化 , 2020 , 44 ( 20 ): 11 - 18 .
ZHANG Yan , CHEN Qixin , GUO Hongye , et al . Equilibrium analysis of power capacity market incorporating investment decision [J]. Automation of Electric Power Systems , 2020 , 44 ( 20 ): 11 - 18 .
BOYD S , VANDENBERGHE L , FAYBUSOVICH L . Convex optimization [J]. IEEE Transactions on Automatic Control , 2006 , 51 ( 11 ): 1859 .
HOBBS B F , METZLER C B , PANG J S . Strategic gaming analysis for electric power systems: an MPEC approach [J]. IEEE Transactions on Power Systems , 2000 , 15 ( 2 ): 638 - 645 .
席磊 , 余涛 , 张孝顺 , 等 . 基于狼爬山快速多智能体学习策略的电力系统智能发电控制方法 [J]. 电工技术学报 , 2015 , 30 ( 23 ): 93 - 101 .
XI Lei , YU Tao , ZHANG Xiaoshun , et al . A fast multi-agent learning strategy base on DWoLF-PHC( λ ) for smart generation control of power systems [J]. Transactions of China Electrotechnical Society , 2015 , 30 ( 23 ): 93 - 101 .
荆朝霞 , 杨莹 . EWA算法在电力市场仿真中的应用 [J]. 电力系统自动化 , 2010 , 34 ( 24 ): 46 - 50 .
JING Zhaoxia , YANG Ying . Application of the EWA algorithm in electricity market simulation [J]. Automation of Electric Power Systems , 2010 , 34 ( 24 ): 46 - 50 .
孙培博 , 周明 , 张磊 , 等 . 基于ABM仿真的实时市场结算不平衡费用分析 [J]. 电力系统自动化 , 2022 , 46 ( 5 ): 171 - 182 .
SUN Peibo , ZHOU Ming , ZHANG Lei , et al . Analysis of unbalanced cost in real-time market settlement based on agent-based model simulation [J]. Automation of Electric Power Systems , 2022 , 46 ( 5 ): 171 - 182 .
李涛 , 胡维昊 , 李坚 , 等 . 基于深度强化学习算法的光伏-抽蓄互补系统智能调度 [J]. 电工技术学报 , 2020 , 35 ( 13 ): 2757 - 2768 .
LI Tao , HU Weihao , LI Jian , et al . Intelligent economic dispatch for PV-PHS integrated system: a deep reinforcement learning-based approach [J]. Transactions of China Electrotechnical Society , 2020 , 35 ( 13 ): 2757 - 2768 .
MNIH V , KAVUKCUOGLU K , SILVER D , et al . Human-level control through deep reinforcement learning [J]. Nature , 2015 , 518 ( 7540 ): 529 - 533 .
SILVER D , LEVER G , HEESS N , et al . Deterministic policy gradient algorithms [C]// International Conference on Machine Learning , June 21-26 , 2014 , Beijing, China .
YE Y J , QIU D W , SUN M Y , et al . Deep reinforcement learning for strategic bidding in electricity markets [J]. IEEE Transactions on Smart Grid , 2020 , 11 ( 2 ): 1343 - 1355 .
LIANG Y C , GUO C L , DING Z H , et al . Agent-based modeling in electricity market using deep deterministic policy gradient algorithm [J]. IEEE Transactions on Power Systems , 2020 , 35 ( 6 ): 4180 - 4192 .
骆子雅 , 季天瑶 , 荆朝霞 , 等 . 电力差价合约机制设计与应用 [J]. 电网技术 , 2019 , 43 ( 8 ): 2743 - 2751 .
LUO Ziya , JI Tianyao , JING Zhaoxia , et al . Design and application of contract for difference in electricity market [J]. Power System Technology , 2019 , 43 ( 8 ): 2743 - 2751 .
GUO H Y , CHEN Q X , XIA Q , et al . Electricity wholesale market equilibrium analysis integrating individual risk-averse features of generation companies [J/OL]. Applied Energy , 2019 , 252 [ 2021-08-11 ]. https://doi.org/10.1016/j.apenergy. 2019.113443 https://doi.org/10.1016/j.apenergy.2019.113443 .
CHOW Y , GHAVAMZADEH M . Algorithms for CVaR optimization in MDPs [EB/OL]. [ 2021-09-20 ]. https://arxiv.org/pdf/1406.3339.pdf https://arxiv.org/pdf/1406.3339.pdf .
袁智强 . 电力市场纳什均衡与风险回避理论的研究 [D]. 上海 : 上海交通大学 , 2004 .
YUAN Zhiqiang . Studies on Nash equilibrium and risk evasion in electricity market [D]. Shanghai : Shanghai Jiao Tong University , 2004 .
张少华 , 李渝曾 , 周永兴 , 等 . 考虑电力差价合同的发电厂报价策略研究 [J]. 电力系统自动化 , 2000 , 24 ( 8 ): 15 - 18 .
ZHANG Shaohua , LI Yuzeng , ZHOU Yongxing , et al . Strategic bidding of power generators in electricity market with contracts for differences [J]. Automation of Electric Power Systems , 2000 , 24 ( 8 ): 15 - 18 .
BODIE Z , KANE A , MARCUS A J . Investments [M]. 10th ed . New York, USA : McGraw-Hill Education , 2014 : 770 - 799 .
张琛 , 颜伟 . 差价合同分解算法的市场力抑制作用分析 [J]. 电网技术 , 2019 , 43 ( 8 ): 2718 - 2725 .
ZHANG Chen , YAN Wei . Research on impact of decomposition algorithms for CfD on mitigating market power [J]. Power System Technology , 2019 , 43 ( 8 ): 2718 - 2725 .
张粒子 , 王进 , 陈传彬 , 等 . 电力现货市场环境下政府授权差价合同结算机制研究 [J]. 电网技术 , 2021 , 45 ( 4 ): 1337 - 1346 .
ZHANG Lizi , WANG Jin , CHEN Chuanbin , et al . Settlement mechanism of CFDs authorized by government under environment of electricity spot market [J]. Power System Technology , 2021 , 45 ( 4 ): 1337 - 1346 .
LOWE R , WU Y , TAMAR A , et al . Multi-agent actor-critic for mixed cooperative-competitive environments [EB/OL]. [ 2021-09-04 ]. https://arxiv.org/abs/1706.02275 https://arxiv.org/abs/1706.02275 .
CHOW Y , GHAVAMZADEH M , JANSON L , et al . Risk-constrained reinforcement learning with percentile risk criteria [J]. Journal of Machine Learning Research , 2017 , 18 ( 1 ): 6070 - 6120 .
BAYDIN A G , PEARLMUTTER B A , RADUL A A , et al . Automatic differentiation in machine learning: a survey [J]. Journal of Machine Learning Research , 2018 , 18 ( 1 ): 1 - 43 .
杨建林 , 严正 . 求解计及输电约束的线性供给函数均衡模型的分支定界方法 [J]. 中国电机工程学报 , 2010 , 30 ( 13 ): 94 - 100 .
YANG Jianlin , YAN Zheng . Branch and bound approach to the solution of the linear supply function equilibrium model in presence of network constraints [J]. Proceedings of the CSEE , 2010 , 30 ( 13 ): 94 - 100 .
KINGMA D P , BA J . Adam: a method for stochastic optimization [EB/OL]. [ 2021-09-05 ]. https://arxiv.org/pdf/1412.6980.pdf https://arxiv.org/pdf/1412.6980.pdf .
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