Zhitong Chen ^1,2 Rong Jia ³ Songkai Wang ^2* Haipeng Nan ⁴ Liangliang Zhao ^2,3 Xingang Zhang ⁵ Shaoyi Hu ² Qin Xu ²

• ¹ School of Water Resources and Hydropower, Xi'an University of Technology, Xi'an, China
• ² TBEA Sunoasis Co., Ltd, Urumqi, China
• ³ School of Electrical Engineering, Xi’an University of Technology, Xi’an, China
• ⁴ School of Water Resources and Hydropower, Xi’an University of Technology, Xi’an, China
• ⁵ TBEA Co., Ltd, Changji, China

With the increase in the number of microgrids in the same distribution area, they belong to dif-ferent subjects of interest, forming a multi-subject game pattern. Considering the interests of distribution networks and microgrids, a distribution network-multi-microgrid master-slave game model is established by selecting distribution networks as game masters and microgrids as game slaves. A master-slave game equilibrium algorithm based on Kriging metamodel is proposed. The method replaces the microgrid energy internal management model with a proposed Kriging metamodel. In the iterative optimization process, the particle swarm optimization algorithm is used to generate new sampling points and modify the model in a targeted way, so as to quickly and accurately obtain the transaction price and output plan of each microgrid. The algorithm does not need all the parameters of the microgrid, which not only achieves the purpose of protecting the privacy of the microgrid but also avoids a large number of calls to the lower optimization model, effectively reducing the amount of computation, and improves the efficiency of the solution. The results show that the overall operating costs of the microgrids are reduced by 1.4%, 4.6%, and 1.6%, respectively, which effectively balances the interests of multiple parties in the microgrid system; the revenue of the distribution network is increased by 50.6%.