Multi-Objective Optimization Scheduling of Active Distribution Network Considering Large-Scale Electric Vehicles Based on NSGAII-NDAX Algorithm.

With the rapid growth of electric vehicle (EV) ownership, problem increased peak loads on distribution networks due to large-scale EV integration needs be addressed. This study proposes an active network multi-objective optimization scheduling method. It takes into account charging demands EVs and aims minimize operating costs, reduce net load variance, maximize photovoltaic (PV) consumption rate. First, Monte Carlo sampling method is used analyze a large number EVs. Next, we construct model for network. integrates with constraints To tackle problem, propose NSGAII-NDAX algorithm. Additionally, employ fuzzy theory-based select Pareto optimal solution set, addressing challenge decision-making complexity posed by size information-rich content set. Finally, effectiveness proposed in comparative analysis multiple scenarios verified improved IEEE 33-node example. The experimental results show that can effectively utilize peak-to-valley difference system while ensuring system’s economic operation maximum PV Compared other algorithm, algorithm has stronger ability better handle problems.