Optimal Scheduling of Electric Vehicle Loads Based on Multi-Strategy Improved Coati Optimization Algorithm

In order to solve the problem of excessive distribution grid load power caused by the superposition of disorderly charging of electric vehicles (EV) and user base load peaks, we propose to establish a cloud-side-end cooperative optimization scheduling framework based on the theory of cloud-side coordination and big data technology. Firstly, based on the cloud-side collaboration theory and big data technology, a cloud-side-end collaborative optimization scheduling framework is established with comprehensive interconnection and interoperability of distribution grids, charging station operators, smart charging piles and EV users' information; secondly, a charging scheduling mechanism for EV users that takes into account the minimum acceptable profit or maximum cost of the users is proposed; and then a two-layer multi-objective charging/discharging optimization and control model is established from the perspective of the grid-side and the user-side to propose Improved Coati Optimization Algorithm (ICOA) with multiple strategies; finally, the model is solved by applying MATLAB using the load data in the commercial area. The simulation results verify the validity and superiority of the proposed model and method.