Currently, the microgrid operators try to operate this special type of the electrical grid in an optimal way due to the energy and cost saving and enhancing the other technical, environmental and economic aspects. Two of the most important tasks of operators to improve the efficiency of the microgrid are the optimal unit commitment and the distribution feeder reconfiguration. If these tasks are individually carried out, it may not lead to the optimal operation. Simultaneously, performing these two tasks in an unbalanced microgrid is a challenging multi-objective problem that this paper is faced with it. The assumed unbalanced microgrid has been equipped by two hybrid energy systems which include the dispatchable distributed generations that are fuel cell units and the non-dispatchable ones that are wind turbines and photovoltaic cells. The stochastic behavior of the non-dispatchable generation units and electrical demand is modeled by a stochastic copula scenario-based framework. The objective functions are minimization of the operational cost of the microgrid, minimization of active power loss, maximization of voltage stability index, minimization of emissions, and minimization of the voltage and current unbalance indices subject to diverse technical constraints. The proposed multi-objective problem is optimized by multi-objective covariance matrix adaption-evolution strategy (MOCMA-ES) algorithm, and a set of Pareto solutions is achieved. The best compromised solution is then chosen by using the fuzzy technique. The capability of the proposed model is investigated on an unbalanced 25-bus microgrid. The simulation results show the efficacy of the proposed model to optimize objective functions, while the constraints are satisfied.

当前，由于节省能源和成本并增强其他技术，环境和经济方面，微电网运营商试图以最佳方式操作这种特殊类型的电网。操作员提高微电网效率的两个最重要任务是最佳机组投入和配电馈线的重新配置。如果单独执行这些任务，可能不会导致最佳操作。同时，在不平衡的微电网中执行这两个任务是本文面临的具有挑战性的多目标问题。假定的不平衡微电网已经配备了两个混合能源系统，其中包括可调度的分布式发电（即燃料电池单元）和不可调度的分布式发电系统（即风力涡轮机和光伏电池）。不可调度发电单元的随机行为和电力需求是通过基于随机copula情景的框架建模的。目标功能是最小化微电网的运营成本，最小化有功功率损耗，最大化电压稳定指数，最小化排放以及最小化受各种技术约束的电压和电流不平衡指数。通过多目标协方差矩阵自适应进化策略（MOCMA-ES）算法对提出的多目标问题进行了优化，得到了一组Pareto解。然后使用模糊技术选择最佳折衷解决方案。在不平衡的25总线微电网上研究了所提出模型的能力。