Optimized Scheduling of Flexibility Resources for Source-Grid-Load-Storage Based on Improved Wind-Solar Scenario Clustering

In response to the issues of voltage fluctuations and increased system losses caused by the volatility of wind and solar generation in the optimal scheduling of source-grid-load-storage, an optimized scheduling method for flexibility resources based on improved wind-solar scenario clustering is proposed. Firstly, an improved wind-solar scenario clustering algorithm is introduced, which combines density noise-based spatial clustering (DBSCAN) and iterative self-organizing data analysis (ISODATA) techniques to achieve accurate clustering and optimization of wind-solar scenarios. The clustering performance is evaluated using the DB index, Dunn index, and silhouette coefficient to ensure the scientific and stable results. Secondly, considering the crucial role of flexibility resources in source-grid-load-storage scheduling, an optimization model based on flexibility resources is proposed. Finally, the effectiveness of the proposed method is verified through simulations on the IEEE 33-bus system. The results show that the optimized scheduling method can significantly improve the scheduling efficiency of flexibility resources, reduce operational costs, and ensure the stability and sustainability of coordinated source-grid-load-storage operation in a low-carbon economy context.