An active distribution network optimization method considering new energy scenario access and electric vehicle transportation loads

Abstract China’s rapid renewable energy growth has introduced challenges to the stability and reactive power balance of distribution networks due to the uncertainty of wind and photovoltaic (PV) output and the integration of flexible transportation loads. To address these issues, this paper presents an optimization method for active distribution networks. A Monte Carlo-based scenario simulation and a fast scenario reduction technique are used to manage wind and PV uncertainty. Additionally, an optimization model for reactive power is developed to minimize active power losses and voltage deviations while integrating wind, PV, and transportation loads. The model, solved via an improved second-order cone programming method using the GUROBI solver, optimizes transportation load configuration over time. Simulation results based on the IEEE 33-bus system show that the method enhances voltage quality and reduces network losses, achieving cost and efficiency improvements.