Bilayer game strategy of regional integrated energy system under multi-agent incomplete information

Abstract

In view of the high coupling degree of regional integrated energy system, a bilayer interaction strategy, consisting of energy suppliers, distribution networks, and users, is proposed. Game interaction strategy includes two aspects: scheduling and bidding. The independent system operator (ISO) coordinates all adjustable resources. Depending on the quotation price and multi-energy load prediction, ISO minimises the total energy cost, which realises the complementary of the multi-energy in the cooperative game. Under the assumption of incomplete information and bounded rationality, this study designs bidding functions and pay-as-bid settlement protocols. On this basis, according to history scheduling data and units’ characteristics, agents for energy suppliers pursue maximum interests. Also, the non-cooperative bidding process in multi-energy market is simulated by using Q-learning algorithm. Finally, the evolutionary process of the bilayer competitive game model is studied by practical example, and the existence local Nash equilibrium of the strategy is also proven.

Keywords

• pricing
• power markets
• game theory
• multi-agent systems
• tendering
• scheduling
• learning (artificial intelligence)
• evolutionary computation
• noncooperative bidding process
• multienergy market
• bilayer competitive game model
• bilayer game strategy
• regional integrated energy system
• multiagent incomplete information
• high coupling degree
• bilayer interaction strategy
• energy suppliers
• game interaction strategy
• scheduling
• independent system operator
• multienergy load prediction
• bidding functions
• pay-as-bid settlement protocols
• total energy cost minimization
• ISO coordinates
• quotation price
• bounded rationality
• unit characteristics
• history scheduling data
• Q-learning algorithm
• evolutionary process
• local Nash equilibrium
• distribution networks