Evaluation of Power System Energy Storage Operation Configuration Based on Multi-Objective Optimization

In the context of the “carbon neutrality” goal, future power systems will inevitably rely on a high percentage of renewable energy. However, since the output power of renewable energy systems is highly stochastically volatile, this will have a big impact on the real-time balance of the system. To ensure the real-time balance of power system output power with a high percentage of renewable energy sources, optimize the power distribution plan, and increase economic efficiency, we first propose a control method to enhance the operational stability of wind turbines by controlling the system power, frequency regulation, and optimal load shedding operation under random wind conditions. Second, the Robust Multiple Reserve Scheduling (RMRS) model is established to optimize the energy storage configuration. This model enables decision-makers to make optimization decisions from a multi-objective perspective by simultaneously optimizing multiple subsystems. The Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) algorithm is then employed to achieve an optimal balance among the different objectives, providing decision-makers with a range of feasible trade-off solutions. Finally, a case study conducted on IEEE30 nodes validates the effectiveness and practical application value of the proposed model in efficiently optimizing power system configurations.