Low-carbon Operation Optimization of Multi-energy Microgrid Based on Hybrid Game

• 1、School of Automation, Guangdong University of Technology, Guangzhou 510006,

Abstract：Aiming at the collaborative optimization problem of low-carbon operation of multi-energy microgrid (MEMG) under distribution network, a hybrid game model with the goal of maximizing the benefits of each entity is constructed, aiming to formulate the power price through the distributed system operator (DSO) to coordinate the MEMG alliance\'s energy storage charging and discharging, load demand response, and peer-to-peer (P2P) electrical energy trading and thermal energy trading. Firstly, a DSO and MEMG alliance master-slave game model embedded in MEMG alliance cooperative game is established. Among them, DSO is the leader, aiming to maximize its benefits, and guides the low-carbon operation of the MEMG alliance by setting electricity prices; The MEMG alliance is a follower, aiming to maximize its benefits, responding to DSO\'s strategy through cooperation, and using generalized Nash bargaining theory to fairly distribute the benefits of the Alliance according to the contribution of each subject of the alliance members. Next, the genetic algorithm combined with the alternating direction multiplier method (ADMM) is used to solve the proposed model. The results show that the hybrid game model not only effectively coordinates the low-carbon operation of the MEMG alliance, but also distributes the benefits generated by cooperation according to the "asymmetric" contribution of alliance members, which can improve the enthusiasm of Alliance members.

Keywords： Electrical Theory and New Technologies multi-energy microgrid hybrid game theory generalized nash bargaining theory bargaining power carbon trading