A reliability-based stochastic planning framework for AC-DC hybrid smart distribution systems

Abstract

This paper introduces a stochastic multi-objective optimization model for the planning of AC-DC hybrid smart distribution systems (DSs). The proposed model determines the optimal AC-DC network configuration that achieves two main objectives: (1) minimizing system costs, and (2) maximizing system reliability. The second objective is achieved through the minimization of the expected energy not supplied. Network buses and lines can become either AC or DC in order to achieve the planning objectives. The model features a Monte-Carlo simulation (MCS) for addressing stochastic variations related to load demands and renewable distributed generators (DGs). The hybrid planning problem has been solved by means of a multi-objective genetic algorithm, and the trade-off between the DS costs and reliability has been evaluated using the Pareto optimality concept. The proposed model has been tested using a case study involving a hybrid DS that included a variety of types of loads and DGs. Solving the same case study using a traditional AC planning technique provided verification of the benefits offered by the proposed model, whose efficacy was confirmed through a comparison of the AC and hybrid Pareto fronts.