Enhancing Distribution System Pliability and Planning with Distributed Generators Using Fuzzy Firefly Optimization

Abstract

Traditional power grids experience significant energy loss during distribution. Distributed generation (DG) technologies offer a promising solution by introducing smaller power sources closer to demand centers. These localized sources relieve a certain pressure on centralized power plants that reduces transmission losses. However, improper sizing and on-site placement of DGs can cause technical challenges, economic drawbacks, and environmental concerns. Historically, the process of identifying optimal sites and capacities for DGs has presented grid operators with formidable computational challenges, intensifying their workload. Nonetheless, the advent of sophisticated optimization software has revolutionized this task, offering a more efficient and manageable solution for operators navigating the complexities of grid management. This research deals the utilization of a fuzzified firefly optimization (FFO) algorithm to enhance the allocation of distributed generators (DGs) within a distribution system. Through strategic placement of diverse DG types, the FFO strategy targets the minimization of both real and reactive power losses. Subsequently, the study assesses the influence of this optimization on critical system performance metrics. To gauge the efficacy of the approach across varied load conditions, the investigation integrates different DG types into an IEEE 85-bus test system and conducts simulations spanning from below-rated (0.5) to above-rated (1.5) load capacities.