A Hybrid Approach for Security‐Constrained Unit Commitment Based on Relaxation Strategies and Adjustment Technique

With the advancement of power systems and the increasing demand for electricity, the expansion of unit scales has intensified the complexity of dispatch optimization. Therefore, the goal of this paper is to efficiently address the large‐scale security‐constrained unit commitment (SCUC) problems and achieve near‐optimal solutions. First, this paper introduces a ramp rate adjustment coefficient based on a traceable approximate unit commitment (UC) model to enhance the discretization of unit output. The optimal adjustment coefficient is accurately evaluated through comprehensive performance metrics. Second, utilizing the initial solution generated from the improved model, appropriate relaxation strategies are employed to provide additional adjustment space for further optimization. Finally, by fixing the start‐up and shut‐down variables of the majority of units and integrating a local search algorithm, the high quality and feasibility of the final solution are ensured. The efficiency and accuracy of solving the scheduling problem is improved by increasing the discretization of the model, relaxing, and fixing certain unit states. Simulation results based on IEEE standard system data show that the proposed method markedly enhances computational efficiency and precision in addressing real large‐scale UC problems compared to traditional UC models.