OPTIMIZATION STRATEGY FOR LOW-CARBON COOPERATION OF MULTI-DISTRICT INTEGRATED ENERGY SERVICE PROVIDERS CONSIDERING DYNAMIC PRICING AND CARBON TRADING

被引：0
|
作者：
Li R. [1 ]
Lyu H. [1 ]
Peng X. [1 ]
Wang B. [1 ]
Zhu J. [2 ]
机构：
[1] College of Electrical and Electronic Engineering, North China Electric Power University, Baoding
[2] College of Economic and Management, North China Electric Power University, Beijing
来源：
Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2024年 / 45卷 / 03期
关键词：
carbon trading; dynamic pricing; integrated energy markets; multi- district integrated energy service providers; Nash bargaining;
D O I：
10.19912/j.0254-0096.tynxb.2022-1751
中图分类号：
学科分类号：
摘要：
To address the issues of benefit distribution and dynamic pricing brought about by the participation of multi- district integrated energy service providers（MDIESP） in the integrated energy and carbon trading markets，this paper proposed a new cooperative trading framework for MDIESP. Firstly，a collaborative trading mechanism for MDIESP was designed under the stepped carbon trading mechanism. Dynamic pricing was formulated for the upper- level regional retail market to guide the energy purchase behavior of each district service provider. Secondly，under the gradual construction of a new power system，the carbon quota and emission model was improved according to the change in the proportion of new energy，and the carbon emissions of each district were constrained through a stepped carbon trading mechanism in the market. Finally，a Nash bargaining model was established for multi-district service providers，decomposing the model into sub-problems of alliance cost minimization and negotiation of electricity and heat trading payments. It proves that the proposed model and method can improve the initiative of each district to participate in the coalition and effectively reduce the carbon emission and total operation cost of each district. © 2024 Science Press. All rights reserved.
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页码：337 / 346
页数：9
相关论文
共 22 条
  • [1] DING T, Et al., Review of energy Internet and its operation［J］, Proceedings of the CSEE, 38, 15, pp. 4318-4328, (2018)
  • [2] Bi- level equilibrium of energy retailer- smart energy hub game in integrated energy market［J］, IET smart grid, 4, 3, pp. 284-296, (2021)
  • [3] LI P，, MA X Y，, GUO Z G，, Et al., Game strategy of integrated energy service providers based on bi- level optimization［J］, Power system technology, 45, 2, pp. 460-469, (2021)
  • [4] TAN J J, LI Y., Review on transaction mode in multi-energy collaborative market［J］, Proceedings of the CSEE, 39, 22, pp. 6483-6497, (2019)
  • [5] WANG J X, LI G Y，, Et al., Mechanism design for integrated energy markets mechanism based on multi-market equilibrium［J］, Proceedings of the CSEE, 41, 17, pp. 5789-5803, (2021)
  • [6] LIU D N，, LIANG J H., Integrated energy service business operation model and key issues research and prospects［J］, IOP conference series：earth and environmental science, 680, 1, (2021)
  • [7] WANG J, WANG S Z，, Et al., Integrated energy purchase- sale decision making and scheduling for integrated energy service provider considering user grading dynamic combination［J］, E3S web of conferences, 160, (2020)
  • [8] MU C L, DING T, LI L, Coordinated optimization operation model of multiple load- serving entities and energy supply companies based on two- level distributed scheduling［J］, Power system technology, 45, 11, pp. 4336-4344, (2021)
  • [9] WEI C, WANG G F，, Et al., Non- cooperative game- based optimal operation method of multiple energy hubs［J］, Electric power automation equipment, 40, 11, pp. 48-53, (2020)
  • [10] HUANG Y J, LIU N., A two- stage energy management for heat- electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization［J］, Energy, 244, (2022)
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