Multi-Source Coordinated Fault Recovery Strategy for Flexible Distribution Networks with SOP

The issue of large-scale power outages in electrical systems triggered by extreme natural disasters, cyber-attacks, and cascading failures—characterized as high-risk, low-probability (HILP) events—requires an effective solution. A flexible distribution network multi-source collaborative fault recovery strategy is proposed, which is based on intelligent soft switches, distributed power sources, and energy storage systems. First, a Gaussian Mixture Model (GMM) is used to model the uncertainty in source-load power forecasting, capturing the random fluctuations in load and distributed power source outputs. Next, considering the characteristics of distributed power sources, energy storage systems, and loads, a fault recovery model for flexible distribution networks containing intelligent soft switches is developed. To improve solving efficiency, the model is converted into a second-order cone programming (SOCP) problem using second-order cone relaxation, and a two-stage algorithm is applied for the solution. Finally, validation with an improved IEEE 33-bus system shows that this strategy effectively enhances the recovery capability of the distribution network during extreme events, with significant advantages in improving load recovery rates and voltage quality.