Combined Framework with Heuristic Programming and Rule-Based Strategies for Scheduling and Real Time Operation in Electric Vehicle Charging Stations

This paper proposes a flexible framework for scheduling and real time operation of electric vehicle charging stations (EVCS). The methodology applies multi-objective evolutionary particle swarm optimization algorithm (EPSO) vehicles (EVs) based on day-ahead scenario. Then, is managed rule-based (RB) approach. Two types consumer were considered: EV owners with request (scheduled consumers, SCh) non-scheduling users (NSCh). EPSO has two main objectives: cost reduction reduce overloading high demand in grid. EVCS support by photovoltaic generation (PV), battery energy storage systems (BESS), the distribution method allows selection between three charging, distributing it according to demand. model estimates SC remaining state charge (SoC) arriving then adjusts actual difference RB. results showed profit proposed technique. RB have fast solution problem that practical implementation.