Online optimal dispatch based on combined robust and stochastic model predictive control for a microgrid including EV charging station

To achieve carbon neutrality and meet the increased charging demand of electric vehicles, microgrids incorporating renewable energy and charging stations are considered one of the potential solutions. However, the inevitable uncertainties of renewable energy and load demand become a challenge for the online charging dispatch of the microgrid. Considering these uncertainties, this paper proposes a two stage optimal framework for the online dispatch of a grid-connected DC microgrid. The first stage presents a power coordination model to obtain the schedule plans of the main grid, the energy storage unit and the charging station, where the combined robust and stochastic model predictive control approach with different granular models is developed to solve this problem and effectively deal with these uncertainties. In the second stage, the charging station allocation model is designed to determine the charging power for every EV, which takes into account the max-min fairness of the charging power. Numerical cases in the presence of uncertainties are studied to evaluate the proposed dispatch framework and the solving approaches. The simulation results show its superiority in both computational efficiency and operating cost.(c) 2022 Published by Elsevier Ltd.

Automated summary

This paper proposes a two-stage optimal framework for the online dispatch of a grid-connected DC microgrid, aiming to address the uncertainties of renewable energy and load demand. The framework includes a power coordination model and a charging station allocation model, and its superiority is validated through numerical case studies.