Multi-Objective Optimal Scheduling for Energy Storage-Integrated Power Systems Considering Coordinated Enhancement of Power Supply Capacity and Renewable Energy Accommodation Capability

With the increasing penetration of renewable energy sources, the uncertainty in power generation systems has intensified, necessitating the comprehensive utilization of energy storage systems and conventional power units to enhance power system power supply reliability and renewable energy accommodation capacity while maintaining power balance. To address these challenges, this study proposes a systematic approach: First, the reserve availability assessment model is refined by considering the simultaneity of reserve demand generation. Subsequently, a multi-objective optimal scheduling framework incorporating energy storage is developed to simultaneously improve power supply capability and renewable energy absorption. The normalized normal constraint (NNC) method is employed to obtain Pareto-optimal solutions, followed by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) analysis for final decision-making. Case studies demonstrate the proposed scheduling scheme's adaptability to net load forecasting errors and reveal operational characteristic differences among energy storage systems at various grid connection nodes through comparative analysis of generation schedules and reserve capacities.