Optimization of Load-Storage Cooperative Control for Microgrids

This study is dedicated to introducing controllable source loads in DC microgrids and incorporating them into the energy storage control system as virtual energy storage. This offers a feasible solution for achieving the synergistic optimization of source-load storage energy. Initially, we model wind turbines and desalination loads as virtual energy storage equivalents. Recognizing electric vehicles as both mobile loads and possessing energy storage characteristics, we developed an organized charging and discharging model using the tariff mechanism to represent the virtual energy storage of electric vehicles. Subsequently, we integrate source-load storage and establish an economic optimization model for the virtual energy storage system to maximize intraday microgrid operation revenue. This results in a set of energy co-optimization control strategies with virtual capacitance value and virtual charge state as operating parameters for each time period. Ultimately, the effectiveness of the source-load-storage energy co-optimization control is verified through simulation. This not only alleviates the regulation pressure on energy storage within the DC microgrid but also significantly improves the microgrid's operating economy.