Two-layer optimal scheduling of distribution network-multi-microgrids based on master–slave game

Abstract

With the increase in the number of microgrids in the same distribution area usually belong to different 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 a 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 both achieves the purpose of protecting the privacy of the microgrid and avoids a large number of calls to the lower optimization model, effectively reducing the amount of computation and improving the efficiency of the solution. The results show that the overall operating costs of the three microgrids used in the case study 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%.