To enhance the profitability of wind storage power stations under spot electricity pricing, an initial step involves establishing a foundational optimal scheduling model specific to these conditions. Subsequently, this model is refined to incorporate the operational states commonly encountered, such as power restrictions, load protocol power supply, and power assessments at the grid connection point. Each scenario's optimal scheduling model is meticulously developed to address these variables. Utilizing data from a wind power storage station located in northwest China, the commercial solvers are employed to derive the optimal scheduling solutions and evaluate the financial performance under various scenarios. The findings reveal that, compared to the scenario without energy storage as a benchmark, model optimization yields a revenue increase of 9.54% under spot pricing. Moreover, when accounting for the centralized energy storage grid connected end power restriction, distributed energy storage grid connected end power restriction, load protocol power supply, and power assessments, the revenue enhancements are 6.11%, 6.74%, 7.31%, and 10.56%, respectively. This study demonstrates that by mitigating the adverse impacts of these diverse operational conditions, a substantial improvement in the overall financial returns of wind storage power stations can be achieved. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
Zhu et al. (Thu,) studied this question.