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Academic Journal of Business & Management, 2021, 3(8); doi: 10.25236/AJBM.2021.030813.

Market trading model before the distribution network under the participation of multi-interest parties at the early stage of marketization


Wenxu Tian

Corresponding Author:
Wenxu Tian

CHN Energy Longyuan Power Technology & Engineering Co., Ltd.  Haidian Beijing, 100039, China


Along with the promotion of the electricity sales side market reform, load-side resources, including new energy sources, gradually participate in the distribution network electricity sales market. At the early stage of marketization, in order to give full participation rights to all parties involved in the market and to take into account the responsibility of distribution network operators to ensure the safety and quality of power supply, we propose a distribution network day-ahead market transaction model with the participation of multiple interests at the early stage of marketization. Firstly, a tripartite interest model including distribution network operators, distributed power supply operators and load aggregators is established in the distribution network, and all three parties take time-of-use tariff as the game strategy; secondly, a Pay as Bid (PAB) model is combined with the tripartite interest model to establish a market settlement model, and the three parties can modify their own offers according to the available information in the market settlement process. Finally, the Nash-Q method is used to solve the model. The results show that, compared with the traditional constant/time-sharing tariff, the model can ensure the safe and reliable power supply to customers while stimulating the active participation of new energy and other market players in the market, and can also increase the contribution of new energy to the power balance and reduce the risk of new energy consumption in the distribution network.


Nash-Q method, distribution network, day-ahead market, game theory

Cite This Paper

Wenxu Tian. Market trading model before the distribution network under the participation of multi-interest parties at the early stage of marketization. Academic Journal of Business & Management (2021) Vol. 3, Issue 8: 72-83. https://doi.org/10.25236/AJBM.2021.030813.


[1] The State Council of People,s Republic of China. Some opinions on further deepening reform of the electric power system[R].2015.

[2] ZOU Peng, CHEN Qixin, XIA Qing, et al. Logical Analysis of Electricity Spot Market Design in Foreign Countries and Enlightenment and Policy Suggestions for China[J].Automation of Electric Power Systems,2014,38(13):18-27. DOI: 10.7500/AEPS20140219003. 

[3] TIAN Shiming, YAN Wenpeng, ZHANG Dongxia,et al.Technical forms and key technologies on energy internet[J].Proceedings of the CSEE,2015,35(14):3482-3494

[4] HU Junjie, WANG Kunyu, AI Xin,et al.Transactive energy:an effective mechanism for balancing electric energy system. Proceedings of the CSEE,2019,39(4):953-966.

[5] 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. DOI:10.7500/AEPS20150922003.

[6] ZHANG Zhonghui, LAI Feiyi, Xie Yimiao. Analysis of trilateral game in electricity market based on Nash equilibrium theory[J]. Power System Technology, 2016,40(12): 3671-3679.

[7] XIA Ye, KANG Chongqing. CHEN Tianen, et al. Day-ahead market mode with power consumers participation in wind power accommodation[J]. Automation of Electric Power Systems, 2015, 39(17): 120-126.DOI:10.7500/AEPS20150317009.

[8] WU Cheng, GAO Bingtuan, TANG Yi, et al. Master-slave Game Based Bilateral Contract Transaction Model for Generation Companies and Large Consumers[J]. Automation of Electric Power Systems,2016,40(22):56-62. DOI: 10.7500/AEPS20151110003.

[9] CHEN Qixin, WANG Kedao, CHEN Sijie, et al. Transactive energy system for distributed agents: architecture, mechanism design and key technologies[J]. Automation of Electric power Systems, 2018,42(3):1-7. DOI:10.7500/AEPS20171031002.

[10] ZHANG Xiaoxuan, XUE Song, YANG Su, et al. International experience and lessons in power sales side market liberalization[J]. Automation of Electric Power Systems, 2016, 40(9):1-8. DOI: 10.7500/AEPS20151128001.

[11] CHEN Yuguo, ZHANG Xuan, LUO Gang, et al. Demand Response Mechanism and Approach of Electricity Spot Market in Bidding Mode without Price on User Side[J].Automation of Electric Power Systems,2019,43(9):179-186. DOI: 10.7500/AEPS20180409009.

[12] Junling Hu, Michael P Wellman. Nash Q-learning for General Sum Stochastic Game [J]. Journal of Machine Learning Research(S1532-4435),2003,4:1039-1069.

[13] WEN Junqiang, ZENG Bo, ZHANG Jianhua. Bi-level Programming Method for Distributed Generator Considering Stakeholders Game Relationship in an Electricity Market Environment[J]. Automation of Electric Power Systems, 2015, 39(15):61-67. DOI: 10.7500/AEPS20141203001.

[14] LIU Guojing, HAN Xueshan, WANG Shang, et al. Optimal decision-making in the cooperation of wind power and energy storage based on reinforcement learning algorithm[J]. Power System Technology, 2016, 40(9): 2729-2736.