Abstract
This paper systematically discusses two-population asymmetric evolutionary games (2PAEGs) from the perspective of decision-making behavior characteristics, and applies these game models to a two-population supply-side electric power bidding market. First, a 2PAEG model is established. Then, complete evolutionary equilibrium rules of this model are revealed during decision-making processes. Discussion shows that final evolutionary game equilibria achieved in the 2PAEG model are only determined by some payoff parameters, which are defined as relative net payoff (RNP) parameters in this paper. Finally, a case study of supply-side bidding simulation for two generator populations is conducted, which can effectively verify the universality and effectiveness of the evolutionary dynamics results obtained in the established general 2PAEG model. Moreover, it shows that reasonable policies made by the government can guide more appropriate power bidding for onto-grid electricity.
Highlights
The energy and electric power systems (EEPS’s) have developed rapidly around the world, such as energy interconnection system, ubiquitous Internet of things in electricity, and integrated energy systems
evolutionary game theory (EGT) is a better mathematical tool to solve the issues of optimal bidding strategy for the generator companies (GENCOs) in an electricity markets (EMs)
Taking China as an example, where GENCOs are independent economic entities and they participate in competition in an EM through the power bidding
Summary
The energy and electric power systems (EEPS’s) have developed rapidly around the world, such as energy interconnection system, ubiquitous Internet of things in electricity, and integrated energy systems. Traditional optimization theory system, which is characterized by single-agent decision-making, cannot better to address this topic To this end, more and more scholars try to investigate this area combining with game theory (GT). GT has gradually become a powerful mathematical tool to solve multi-agent decision-making issues in a competitive EM. EGT is developed based on natural selection mechanisms with strict bounded rationality assumptions It is more suitable for solving practical decision issues, and can better describe the spontaneous evolution process of different populations. EGT is a better mathematical tool to solve the issues of optimal bidding strategy for the GENCOs in an EM. For this motivation, we first systematically investigate the complete evolutionary dynamics of a general two-population evolutionary game (2PAEG).
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