Abstract
This paper introduces a stochastic multi-objective planning model for the network configuration of smart distribution systems (DSs). The primary goal of the proposed model is to determine the network configuration that optimizes both the system cost and reliability. The system reliability is optimized through the minimization of the expected energy not supplied. The model uses a Monte-Carlo simulation (MCS) to enable consideration of the stochastic variations associated with load demands and renewable distributed generators (DGs). The Pareto optimality concept has been used to evaluate the tradeoff between the DS cost and reliability. The proposed model was successfully employed to find the optimal network configuration of a 14-zone DS that included a variety of types of loads and DGs. The Pareto front obtained in the case study provided evaluation for the relationship between the DS cost and reliability.
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