Optimization of Loop Distribution Network Reconfiguration Using Adaptive Modified Firefly Algorithm

Abstract

Distribution network reconfiguration plays an important role in maintaining system performance during fault conditions while minimizing operational losses. This paper presents an Adaptive Modified Firefly Algorithm (AMFA) for determining optimal switching configurations in a distribution network under several feeder fault scenarios. The proposed method evaluates a total of 64 possible switching combinations and demonstrates fast convergence, reaching optimal or near-optimal solutions within only $1-3$ iterations. The results show a significant reduction in power losses from an initial condition of 0.5378 MW to as low as 0.0394 MW, while ensuring that all 14 general loads remain supplied. In addition to solution quality, the computational performance of the method is highly efficient, requiring only 5-7 seconds to obtain the optimal configuration. This is considerably faster than conventional manual operation, which typically takes 10-15 minutes and may not guarantee the minimum loss condition. The findings indicate that the proposed AMFA approach is capable of improving both the speed and accuracy of decision-making in distribution system reconfiguration, making it a practical solution for real-time applications under fault conditions.