Optimal restoration algorithm for active distribution network considering island mode of the microgrids

Abstract

Faults in electrical networks can disrupt power supply to large populations, resulting in significant economic and social repercussions. With the growing integration of active agents such as Microgrids (MGs) and distributed generation (DG) into the electrical grid, it becomes crucial to develop methods that restore power to the maximum number of users in the shortest possible time, while considering the dynamic behavior of the network. This paper introduces a restoration strategy for Active Distribution Networks based on the Binary Grey Wolf Optimization (BGWO) algorithm. The approach accounts for the island operation mode of MGs and leverages the controllability of intelligent electronic devices (IEDs). The fitness function aims to minimize several indicators, including energy not served (ENS), load prioritization, and deviation of the voltage limits. The proposed strategy was validated using a modified IEEE 123-node test feeder with integrated Distributed Energy Resources (DERs), also,it was tested under three approaches: low and high automation penetration of controllable IEDs and special operating conditions such as load variation, topology change and cut off generation. The results demonstrate the effectiveness of the BGWO-based strategy in reducing fitness function in 40% when a high automation penetration is considered. The strategy shows its flexibility and potential for real life applications.