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By optimizing the capacity and running status of the microgrid (MG), HRES can decrease the running cost and improve the efficiency. Such an optimization problem is generally a constrained mixed\u2010integer programming problem, which is usually solved by linear programming method. However, as more and more devices are added into MG, the mathematical model of HRES refers to nonlinear, in which the traditional method is incapable to solve. To address this issue, we first proposed the mathematical model of an HRES. Then, a coevolutionary multiobjective optimization algorithm, termed CMOEA\u2010c, is proposed to handle the nonlinear part and the constraints. By considering the constraints and the objective values simultaneously, CMOEA\u2010c can easily jump out of the local optimal solution and obtain satisfactory results. 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