Stochastic Dynamic Reconfiguration in Smart Distribution System Considering Demand-Side Management, Energy Storage System, Renewable and Fossil Resources and Electric Vehicle

The reconfiguration of the smart distribution grid is one of the low-cost and effective ways to improve loss reduction and voltage balance, which has faced important challenges with the presence of issues such as energy storage systems, electric vehicles, demand side management, and fossil distributed generation resources. In recent studies, in addition to considering the reduction of distribution system losses as one of the goals of the optimization problem, reducing the purchase of power from the transmission network in distribution substations has also been considered by researchers. In this paper, a second-order cone optimization model to solve the stochastic dynamic reconfiguration based on a scenario considering renewable energy resources, energy storage systems, electric vehicles, and demand-side management program with fossil distributed generation such as gas-fired and diesel generators resources to improve a multi-objective function including reducing power losses, reducing power purchases at distribution substations and reducing the cost of cutting off renewable energy resources has been proposed. The proposed model is implemented using the Gurobi solver and the Julia programming language, and the results of the IEEE 33-bus network analysis for the day ahead and the 24 h load curve demonstrate the performance of the proposed model.