Distributed transaction optimization model of multi-integrated energy systems based on nash negotiation

Abstract

Integrated energy system (IES) can achieve multi energy complementarity, but it still faces the problem of energy surplus or shortage. Therefore, there are demands for energy sharing among different IESs, but how to determine the trading quantity and trading price? To address this confusion, a distributed optimization model for multi-IES participating in peer-to-peer (P2P) transactions based on asymmetric Nash negotiation is innovatively proposed. First, to facilitate the energy sharing of several IESs with different structures, a P2P trading framework is designed. Second, to meet the needs of individual rationality and alliance cooperation at the same time, a distributed transaction optimization model based on Nash negotiation is proposed. Considering the discourse power determined by contribution, an asymmetric bargaining mechanism is designed. Third, to protect the privacy and improve solution performance, the improved adaptive step-size alternating direction multiplier algorithm (ADMM) is used for the distributed sequential solution. Finally, the effectiveness of the proposed trading framework, bargaining mechanism, optimization model, and solution algorithm are verified by the implementation of simulation. The simulation results show that: 1) The proposed model and algorithm can assist managers in determining the quantity and price of P2P electricity transactions. 2) Compared with the independent operation mode, the cooperative operation mode has significantly improved the overall interests and individual interests. 3) In distributed transactions, managers only need to submit limited information, which protects the privacy and security of each agent. 4) The asymmetric Nash negotiation mechanism can measure discourse power based on contribution. 5) The improved ADMM has the advantages of stronger convergence performance and faster solution speed.