In order to meet the requirements of information privacy between different operators of regional microgrids as well as to meet the computing challenges brought by large-scale microgrids merging into clusters in the future, Dantzig-Wolfe decomposition (DWD) is proposed to solve the optimal scheduling problem of regional multi-energy complementary microgrid clusters in a decentralized manner, meanwhile, the other three kinds of distributed decomposition algorithms are compared and analyzed. For the bus-type microgrid cluster, this paper verifies the effectiveness of the proposed DWD decomposition algorithm, and the proposed algorithm can converge to the optimal result in fewer iterations in winter scenarios. Unlike the other three kinds of distributed decomposition algorithms, the number of iterations of the DWD algorithm varies a little with the increase of the number of microgrids, which is very suitable for the scenario where large-scale microgrids are merged into clusters in the future.
