Distributed collaborative operation strategies in multi-agent integrated energy system considering integrated demand response based on game theory

As the conflict between energy and the environment intensifies, integrated energy system (IES) is an effective way to reduce tensions with difficulties about multi-energy coupling and multi-agent. This study proposed a multi-agent game operation strategy consisting of energy retailers, suppliers, and users with integrated demand response (IDR). This problem is formulated as a distributed bi-level optimization model with one leader and multi-followers, which is a Stackelberg game among them vertically, and a non-cooperative game between energy suppliers horizontally. The equilibrium of proposed game model is proved the existence and uniqueness, and is solved by a distributed algorithm through genetic algorithm nested quadratic programming. Finally, the effectiveness of the proposed method is verified by the case study in three scenarios. The results shows that the supply-side revenue are effectively improved by 8.57%, the demand-side costs are reduced 1.42% by game model and IDR, and improve the operation and stability of energy supply and utilization.

Automated summary

As the conflict between energy and the environment intensifies, integrated energy system (IES) is an effective solution to address the difficulties of multi-energy coupling and multi-agent. This study proposes a multi-agent game operation strategy with integrated demand response (IDR) to optimize energy supply and utilization. The proposed distributed bi-level optimization model is solved using a distributed algorithm through genetic algorithm nested quadratic programming. Case studies in three scenarios demonstrate the effectiveness of the proposed method in improving supply-side revenue, reducing demand-side costs, and enhancing the operation and stability of energy supply and utilization.