Optimal Operation of Unbalanced Microgrid Utilizing Copula-Based Stochastic Simultaneous Unit Commitment and Distribution Feeder Reconfiguration Approach

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.