Probabilistic planning of the active and reactive power sources constrained to securable-reliable operation in reconfigurable smart distribution networks

Abstract

One of the main goals of SDN is to achieve the desirable operation of a highly secure and reliable network in terms of energy distribution. Hence, this paper presents the probabilistic planning of distributed generations (DGs) and switched capacitive bank (SCB) constrained to the securable-reliable operation (SRO) strategy in reconfigurable SDN. The scheme is formulated as a four-objective optimization problem to simultaneously model the economic, operation, reliability, and security indices of SDN. So that the first to fourth objective minimize the total planning cost and expected operation cost, voltage deviation function (VDF), expected energy not-supplied (EENS), and voltage security index (VSI). It is limited to the AC optimal power flow (AC-OPF) equations, planning and operation model of DG and SCB, formulation of demand response program (DRP), SDN reconfiguration constraints, reliability and voltage security limits. Then, the single-objective model is obtained by using the ε constraint-based Pareto optimization technique. Additionally, the non-parametric probabilistic method models uncertainties of load, energy price, renewable DGs (RDGs) power, and network equipment availability. The strategy is as mixed-integer nonlinear programming (MINLP), where hybrid Krill Herd Optimization (KHO) and Crow Search Algorithm (CSA) achieves a reliable optimal solution. The following provides the planning of different sources based on the SRO strategy with simultaneous formulation of various economic and technical indices considering non-parametric modeling of uncertainties and solving the problem using the mentioned hybrid algorithm presented the contribution in this paper. By implementing this scheme on a 69-bus SDN, the numerical results confirm capability of this scheme in improving the economic, operation, reliability, and security situation of SDN compared to power flow studies. Where it can enhance the mentioned indices up to 16%, 36%, 99%, and 9% taking into account optimal planning and operation of different sources and the DRP compared to the corresponding values obtained by power flow studies.