Dynamic Load Shedding Model for CVaR-Based Reliability Evaluation of Power Systems with Wind Power Integration

Against the backdrop of carbon peaking and carbon neutrality, clean energy has become widespread and continues to develop. Wind power, as a novel energy source, exhibits randomness and fluctuation, posing challenges to the stability, security, and economy of power systems. This study establishes a conditional value-at-risk (CV
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R) model that incorporates wind power generation, contingent on dynamic load shedding. To enhance solution speed, a smoothing(ST) technique is employed to alleviate the maximal function in the objective function. Simulation experiments are conducted using the IEEE-RTS79 system, and numerical results indicate that the application of the ST method leads to faster convergence when solving the model, surpassing both the linear programming (LP) method and the direct solving (DS) method. Furthermore, in comparison with the LP method, the loss of load probability (LOLP) and expected energy not served (EENS) values obtained through model solution are significantly reduced, demonstrating excellent performance. In summary, this study provides an efficient solution for assessing the reliability of integrated renewable power systems, enhancing computational speed, and improving system reliability compared to the LP method.