Flexibility transformation strategy of thermal power units for typical scenario considering wind and solar consumption based on generalized Benders decomposition algorithm

The large-scale integration of wind power and solar power makes the flexibility transformation of traditional thermal power units necessary. In this paper, a flexibility transformation nonlinear programming model considering wind and solar consumption is proposed. To compute the original complicated programming problem efficiently, the generalized Benders decomposition algorithm is used. The original complicated programming problem, which involves month dimension in long-term scheduling and hour dimension in short-term scheduling, is decomposed into one flexibility transformation investment master problem and twelve operation sub-problems. In addition, considering the instability of wind and solar resources, the agglomerative hierarchical clustering algorithm is applied to cluster the typical scenarios. A case study is constructed to verify the validity and applicability of the presented model, and the results are derived. The results show that the model can realize the efficient consumption of wind and solar power while meeting the power demand and the economy, and it is suitable for finding the optimal solution to various parameter settings. Reasonable unit flexibility transformation can also further reduce the total costs, alleviate the curtailment of wind and solar power. The sensitivity of constructed model is also analyzed. Reasonable wind and solar subsidies can promote enterprises to transform the thermal power units and indirectly increase wind and solar consumption. Research in this paper can provide a scientific reference for deciding the flexibility transformation and selecting the flexibility transformation strategy of thermal power units.