Recently, financial issues have been considered as the main aspects of microgrid (MG) evaluation in the literature. In this study, the optimal configuration of the MG has been calculated by presenting a reliability-constrained optimization model. In this optimization approach, the MG units are considered in full available state and random outage state through the planning horizon. To model a proposed MG in details, its uncertainties are formulated in the main function. A combination of Latin hypercube sampling (LHS) algorithm and K-means clustering algorithm is applied to generate all uncertainties. The proposed model simultaneously optimizes two objectives, namely, economic costs and emission performance. Time of use (TOU) based demand response (DR) program has been employed for optimal management of the demand side. At first, the bi-objective function is converted to a sequence of single-objective constrained problems by employing ε-constraints. All Pareto front solutions are obtained by utilizing GAMS for solving the developed mixed-integer linear programming (MILP) model. To make a trade-off among solutions, the max-min fuzzy decision-making method has been used. Due to the positive effect of the DR program on the configuring problem, the total emission and economic costs of MG have been reduced up to 4.01% and 1.72%, respectively.
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