A Coordinated Charging Strategy for Photovoltaic–Energy Storage–Electric Vehicles in Shopping Malls Based on the Modified Bounty Hunter Optimizer

To address the elevated local peak loads, voltage degradation at weak nodes, increased line power flows, and rising operational costs caused by uncoordinated electric vehicle (EV) charging in shopping mall and workplace areas, this paper proposes a coordinated orderly charging method that integrates photovoltaic (PV) generation, an energy storage system (ESS), and EVs based on a two-stage modified bounty hunter optimizer (MIBHO). First, an uncoordinated EV charging load model for the shopping mall and workplace area is constructed using the Monte Carlo method to simulate vehicle arrival times, departure times, initial state of charge (SOC), and target SOC. Next, the mall base load, PV system, ESS, and EV charging station are integrated at node 18 of the IEEE 33-node distribution network, and an orderly charging optimization model is formulated incorporating vehicle time windows, SOC requirements, single-vehicle power limits, and station-level capacity constraints. The proposed MIBHO uses adaptive hierarchical block encoding for coarse search and a refined 24-dimensional hourly search. Without changing daily EV charging energy, it increases peak-PV charging from 52.41% to 69.46%, reduces losses from 4964.0 to 4892.5 kWh, lowers costs from CNY 805.12 to 718.03, and mitigates the evening peak. Classical and CEC2017 tests confirm its competitiveness.