With increasing integration of renewable energy, traditional distribution networks face challenges such as low flexibility, poor response speed, and operational inefficiency. To address these issues, this paper proposes a two-layer optimization framework for active distribution networks that integrates grid reconfiguration and equipment maintenance considerations. The upper layer optimizes the network topology and branch flexibility using a flexibility adequacy index and power loss minimization. The lower layer performs distributed robust dispatch under renewable generation uncertainty. A hybrid algorithm combining Ant Colony Optimization (ACO), Fire Hawk Optimization (FHO), and Differential Evolution (DE) is developed to solve the model efficiently. Simulation is conducted on a modified 62-node test system. Comparative results with deterministic, stochastic, and robust models show that the proposed approach achieves the lowest average cost and maximum cost under 500 Monte Carlo scenarios. It also significantly reduces flexibility deficits and renewable curtailment. In addition, the model contributes to predictive maintenance by identifying optimal switching strategies and branch stress levels. These findings demonstrate the method’s effectiveness in improving economic efficiency, system flexibility, and equipment sustainability.
He et al. (Thu,) studied this question.