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Optimal bidding strategy for PV and BESSs in Joint Energy and Frequency Regulation Markets Considering Carbon Reduction Benefits

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 427-439页

作者： Jing Bian Yuheng Song Chen Ding Jianing Cheng Shiqiang Li Guoqing Li Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education Northeast Electric Power UniversityJilin 132000China Datang Northeast Electric Power Test&Research Institute Co. Ltd.Changchun 130102China

Photovoltaic(PV)and battery energy storage systems(BESSs)are key components in the energy market and crucial contributors to carbon emission reduction *** systems can not only provide energy but can also generate considerable revenue by providing frequency regulation services and participating in carbon *** study proposes a bidding strategy for PV and BESSs operating in joint energy and frequency regulation markets,with a specific focus on carbon reduction benefits.A two-stage bidding framework that optimizes the profit of PV and BESSs is *** the first stage,the day-ahead energy market takes into account potential real-time forecast *** the second stage,the real-time balancing market uses a rolling optimization method to account for multiple ***,a real-time frequency regulation control method is proposed for the participation of PV and BESSs in automatic generation control(AGC).This is particularly relevant given the uncertainty of grid frequency fluctuations in the optimization model of the real-time balancing *** control method dynamically assigns the frequency regulation amount undertaken by the PV and BESSs according to the control interval in which the area control error(ACE)*** case study results demonstrate that the proposed bidding strategy not only enables the PV and BESSs to effectively participate in the grid frequency regulation response but also yields considerable carbon emission reduction benefits and effectively improves the system operation economy.

关键词： Photovoltaic(PV) battery energy storage system(BESS) energy market carbon market frequency regulation service bidding strategy

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bidding strategy for Coordinated Operation of Wind Power Plants and NGG-P2G Units in Electricity Market

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CSEE Journal of Power and Energy Systems 2022年第1期8卷 212-224页

作者： Xiang Gao Ka Wing Chan Shiwei Xia Xian Zhang Guibin Wang Shenzhen Polytechnic ShenzhenChina and also with the Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong KongChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong KongChina School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 102206China School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China

The synergies between electricity and other energy resources could promote energy utilization efficiency in electricity *** this context,this paper proposes a bi-level stochastic optimization model for the joint operation of a coordinated wind power plant(WPP)and natural gas generating(NGG)-power to gas(P2G)suppliers participating in the day-ahead(DA)market and real-time(RT)market as well as providing real-time auxiliary *** coordinated supplier’s payoff is maximized in the upper level with consideration of the uncertainties of WPP output capacity and RT electricity price,while the social welfare of the grid is maximized in the lower *** results demonstrate the effectiveness of the proposed bidding model of the coordinated WPPs and NGG-P2G suppliers by examining its bidding behaviors and benefits with comparisons of four other bidding models.

关键词： Bi-level model bidding strategy WPP NGGP2G uncertainties

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bidding strategy of a Virtual Power Plant Considering Carbon-electricity Trading

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CSEE Journal of Power and Energy Systems 2019年第3期5卷 306-314页

作者： Dechang Yang Shaowen He Qiuyue Chen Dingqian Li Hrvoje Pandzic China Agricultural University BeijingChina Faculty of Electrical Engineering and Computing University of ZagrebCroatia

Virtual power plant(VPP)aggregates large amounts of distributed energy and controllable *** comprehensive consideration of carbon emissions and electricity transactions has great significance in improving the VPP operation’s economic *** this paper,the bidding strategy of the VPP by considering the carbon-electricity integration trading in an auxiliary service(AS)market is *** of all,the basic structure and operating features of the VPP are briefly ***,the bidding strategy model of carbon-electricity integration trading in an auxiliary service market is proposed and the corresponding objective function and the constraint conditions are also ***,the GAMS solver is utilized to give the optimal solution of the bidding strategy ***,the effectiveness of the bidding strategy of a VPP based on the consideration of carbon-electricity integration trading is verified through simulation cases.

关键词： bidding strategy carbon-electricity distribution energy resource integration trading virtual power plant

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Dispatch and bidding strategy of active distribution network in energy and ancillary services market

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Journal of Modern Power Systems and Clean Energy 2015年第4期3卷 565-572页

作者： Yao JIN Zhengyu WANG Chuanwen JIANG Yu ZHANG School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China Guizhou Power Grid Corporation Power Grid Planning&Research Center Guiyang 550002China

The active distribution network(ADN)is able to manage distributed generators(DGs),active loads and storage facilities *** is also capable of purchasing electricity from main grid and providing ancillary services through a flexible dispatching mode.A competitive market environment is beneficial for the exploration of ADN’s activeness in optimizing dispatch and bidding *** a bilateral electricity market,the decision variables such as bid volume and price can influence the market clearing price(MCP).The MCP can also have impacts on the dispatch strategy of ADN at the same *** paper proposes a bilevel coordinate dispatch model with fully consideration of the information interaction between main grid and *** results on a typical ADN validate the feasibility of the proposed method.A balanced proportion between energy market and ancillary services market can be achieved.

关键词： Active distribution network(ADN) Energy market Ancillary services market Optimal dispatch bidding strategy

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A Reinforcement-learning-based bidding strategy for Power Suppliers with Limited Information

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Journal of Modern Power Systems and Clean Energy 2022年第4期10卷 1032-1039页

作者： Qiangang Jia Yiyan Li Zheng Yan Chengke Xu Sijie Chen Shanghai Jiao Tong University Shanghai 200240China Department of Electrical and Computer Science North Carolina State UniversityRaleigh 27695USA

The power market is a typical imperfectly competitive market where power suppliers gain higher profits through strategic bidding *** existing studies assume that a power supplier is accessible to the sufficient market information to derive an optimal bidding ***,this assumption may not be true in reality,particularly when a power market is newly *** help power suppliers bid with the limited information,a modified continuous action reinforcement learning automata algorithm is *** algorithm introduces the discretization and Dyna structure into continuous action reinforcement learning automata algorithm for easy implementation in a repeated *** results verify the effectiveness of the proposed learning algorithm.

关键词： Power market bidding strategy limited information repeated game continuous action reinforcement learning automata

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Market Power of Coordinated Hydro-wind Joint bidding:Croatian Power System Case Study

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 531-541页

作者： Perica Ilak Igor Kuzle Lin Herencic Josip Dakovic Ivan Rajsl the University of Zagreb Faculty of Electrical Engineering and ComputingZagrebCroatia

The paper analyses the coordinated hydro-wind power generation considering joint bidding in the electricity *** impact of mutual bidding strategies on market prices,traded volumes,and revenues has been *** coordination assumes that hydro power generation is scheduled mainly to compensate the differences between actual and planned wind power *** potential of this coordination in achieving and utilizing of market power is *** market equilibrium of asymmetric generation companies is analyzed using a game theory *** assumed market situation is imperfect competition and non-cooperative game.A nu-merical approximation of the asymmetric supply function equilibrium is used to model this *** introduced novelty is the application of an asymmetric supply function equilibrium approximation for coordinated hydro-wind power *** model is tested using real input data from the Croatian power system.

关键词： Asymmetric firm bidding strategy coordination hydro power wind power imperfect competition market power non-cooperative game optimal bidding strategy supply function equilibrium

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Approximating Nash Equilibrium in Day-ahead Electricity Market bidding with Multi-agent Deep Reinforcement Learning

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Journal of Modern Power Systems and Clean Energy 2021年第3期9卷 534-544页

作者： Yan Du Fangxing Li Helia Zandi Yaosuo Xue University of Tennessee KnoxvilleUSA Oak Ridge National Laboratory Oak RidgeUSA

In this paper,a day-ahead electricity market bidding problem with multiple strategic generation company(GEN-CO)bidders is *** problem is formulated as a Markov game model,where GENCO bidders interact with each other to develop their optimal day-ahead bidding *** unobservable information in the problem,a model-free and data-driven approach,known as multi-agent deep deterministic policy gradient(MADDPG),is applied for approximating the Nash equilibrium(NE)in the above Markov *** MAD-DPG algorithm has the advantage of generalization due to the automatic feature extraction ability of the deep neural *** algorithm is tested on an IEEE 30-bus system with three competitive GENCO bidders in both an uncongested case and a congested *** with a truthful bidding strategy and state-of-the-art deep reinforcement learning methods including deep Q network and deep deterministic policy gradient(DDPG)demonstrate that the applied MADDPG algorithm can find a superior bidding strategy for all the market participants with increased profit *** addition,the comparison with a conventional-model-based method shows that the MADDPG algorithm has higher computational efficiency,which is feasible for real-world applications.

关键词： bidding strategy day-ahead electricity market deep reinforcement learning Markov game multi-agent deterministic policy gradient(MADDPG) Nash equilibrium(NE)

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A Deep Reinforcement Learning bidding Algorithm on Electricity Market

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Journal of Thermal Science 2020年第5期29卷 1125-1134页

作者： JIA Shuai GAN Zhongxue XI Yugeng LI Dewei XUE Shibei WANG Limin Department of Automation Key Laboratory of System Control and Information ProcessingShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Coal-based Low-carbon Energy ENN Science and Technology Development Co.Ltd.Langfang 065001China ENN Energy Power Technology(Shanghai)Co. Ltd.Shanghai 201306China

In this paper,we design a new bidding algorithm by employing a deep reinforcement learning *** use the proposed algorithm to estimate conjectural variation of the other firms and then employ this variable to generate the optimal bidding strategy so as to pursue maximal *** this algorithm,electricity generation firms can improve the accuracy of conjectural variations of competitors by dynamically learning in an electricity market with incomplete *** market will reach an equilibrium point when electricity firms adopt the proposed bidding algorithm for a repeated game of power *** simulation examples illustrate the overall energy efficiency of power network will increase by 9.90%as the market clearing price decreasing when all companies use the *** simulation examples also show that the power demand elasticity has a positive effect on the convergence of learning process.

关键词： electricity market reinforcement learning energy efficiency conjectural variation bidding strategy

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A WEIGHTED PRODUCT METHOD FOR bidding STRATEGIES IN MULTI-ATTRIBUTE AUCTIONS

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Journal of Systems Science & Complexity 2010年第1期23卷 194-208页

作者： Mingxi WANG Shulin LIU Shouyang WANG Kin Keung LAI MADIS Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of International Trade and Economics University of International Business and Economics Beijing 100029 China. MADIS Aeademy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China. Department of Management Sciences City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong China.

To eliminate computational problems involved in evaluating multi-attribute bids with differentmeasures,this article first normalizes each individual component of a bid,and then makes use ofthe weighted product method to present a new scoring function that converts each bid into a *** of multi-attribute auction models are introduced in terms of scoring rules and bidding *** bidding strategies,procurer's revenue comparisons and optimal auction designare characterized in these two ***,this article discusses some improvement of robustnessof our models,with respect to the assumptions.

关键词： bidding strategy multi-attribute auctions weighted product method winner determination protocol.

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Strategic Peer-to-peer Energy Trading Framework Considering Distribution Network Constraints

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Journal of Modern Power Systems and Clean Energy 2023年第3期11卷 770-780页

作者： Yanbo Jia Can Wan Biao Li College of Electrical Engineering Zhejiang UniversityHangzhou 310027China

With the development of smart home energy management technology,prosumers are endowed with increased initiative in peer-to-peer(P2P)transactions,bringing new potential for cost *** this study,a novel strategic P2P energy trading framework is proposed considering the impact of network constraints on personal transaction *** can estimate the allowed power injection before engaging in the P2P energy trading,which is solved in a distributed manner based on the sharing form alternating direction method of multipliers(ADMM)*** quantify the network usage cost for each prosumer and promote local transactions among prosumers at the same bus,a modified continuous double auction(CDA)matching algorithm is proposed including a transaction *** adaptive aggressiveness-based bidding strategy is generated considering the risk of uncertainty in real-time energy delivery amount under the limitations of the distribution *** proposed strategic P2P energy trading framework is tested with the IEEE 37-bus distribution network and it is effective in creating profits for prosumers and supporting distribution network operations.

关键词： bidding strategy continuous double auction(CDA) distribution network distributed algorithm peer-topeer(P2P)transaction

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