A novel fault recovery method of active distribution networks oriented to improving resilience - Lei Chen; Yuqi Jiang; Xinyi Deng; Hongkun Chen; Shencong Zheng (Energy Reports, 2022)
Extreme events occur frequently and increase faults in power systems, providing negative effects on the safe and stable operation. In this regard, introducing efficient fault recovery methods to strengthen the resilience of active distribution networks (ADNs) against extreme events is very critical. This paper puts forward a novel fault recovery method for ADNs based on an improved binary particle swarm optimization (BPSO) algorithm, and the topology constraints are specially considered to accelerate the recovery operation. In addition, a resilience evaluation system is built for the ADNs for checking the performance of the proposed fault recovery method. The mathematical model, the fault recovery strategy, as well as the architecture of the resilience evaluation system, are stated in detail. Using MATLAB, an IEEE 33-node system with multiple distributed generators (DGs) is built, and different fault scenarios are imitated for verifying the effectiveness and suitability of the proposed method. From the comparative analysis of the fault recovery schemes with the traditional and improved BPSO algorithms, the proposed method enables to more effectively reduce the node voltage deviation, decrease the power loss and assist the important load recovery. In consequence, the resilience of the ADNs will be appreciatively boosted.