Two-Layer Game Model of Virtual Power Plant Applying CIQPSO Algorithm

doi:10.12204/j.issn.1000-7229.2020.06.002

Abstract

Abstract: In order to make full use of the large-scale energy-storage advantages of electric vehicles （EVs） and the advantages of agent aggregators to flexibly purchase and sell electricity in the power market， to make up for the imbalance between supply and demand in virtual power plant （VPP）， this paper constructs a two-layer game model of a virtual power plant in which electric vehicles participate， to perform internal and external optimization of the virtual power plant at the same time. On this basis， firstly， a fully dynamic game model of the upper-level agent aggregator - virtual power plant is constructed to perform external optimization of the virtual power plant. Secondly， a virtual power plant - electric vehicle aggregator cooperation game model is built to optimize the virtual power plant internals， and the improved Shapley value is used to allocate the cooperation revenue between the virtual power plant and the electric vehicle aggregator. Finally， a virtual power plant with integrated wind turbines， controllable loads， energy storage batteries， users， and electric vehicles is used to analyze the example. The coevolutionary immune quantum partical swarm optimization （CIQPSO） algorithm is used to search for the optimal solution. The results of a numerical example show that the participation of electric vehicles in a virtual power plant can simultaneously improve the both economic benefits and increase the supply-demand balance capability of the virtual power plant.

Key words: virtual power plant（VPP）, electric vehicle（EV）, aggregator, two-layer game, improved Shapley value, coevolutionary immune quantum partical swarm optimization （CIQPSO）algorithm

CLC Number:

TM 73

TAN Zhongfu，TAN Caixia，PU Lei，YANG Jiacheng. Two-Layer Game Model of Virtual Power Plant Applying CIQPSO Algorithm[J]. Electric Power Construction, 2020, 41(6): 9-17.

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