Energy market optimization based on dynamic Pricing

• Published in: Electric power systems research Vol. 210; p. 108172
• Main Authors: Wang, Hui, Jin, Zirong
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2022
• Subjects: Dynamic pricing; Master-slave game; Price response; Virtual power Plant; Dynamic pricing; Price response; Master-slave game; Virtual power Plant
• ISSN: 0378-7796
• DOI: 10.1016/j.epsr.2022.108172

•A master-slave game model considering the uncertainty of source-side output is constructed.•This model reflects the energy interaction between DNO and multiple VPPs, through the game to maximize the interests of both sides.•A master-slave game equilibrium algorithm based on Kriging meta-model is proposed, which can not only protect the privacy of VPP but also improve the solving efficiency. With various social capital gradually into the electric power market, different virtual power plants will belong to different interest subjects in the future. The main development direction of China's energy market is to build a regional comprehensive energy market with multi-agent participation. Because the traditional power grid electricity price adopts monopoly transaction mode, the market enthusiasm is not high. In view of the situation, this paper proposes a two-level optimization model of master-slave game based on dynamic pricing. In order to encourage electric energy transactions between distribution network operators and multiple virtual power plants, distribution network operator solves the internal optimal electricity price according to the price response of virtual power plants in the optimization process. Simulation results show that the proposed strategy can promote energy sharing among integrated energy systems.