Optimal Placement of Shunt Compensator for Power Loss Minimization Using Interval Type 2 Fuzzy Particle Swarm Differential Evolution Algorithm

This study proposes a novel hybrid intelligent optimization algorithm termed interval type 2 fuzzy particle swarm differential evolution (IT2FPSODE), aimed to reducing the active power losses within electrical power system network. The technique employs interval type 2 fuzzy logic control (IT2FLC) which takes the global best fitness as its input and dynamically tunes the inertia weight (w) of particle swarm optimization (PSO) algorithm to avoid local optima trapping, thereby enhancing its global searach capability. Moreover, the crossover and mutation operators from the differential evolution algorithm (DEA) are combined to select the best solution from PSO. This proposed technique optimizes the optimal placement and capacity sizing of the shunt compensator device reactive generation units, and generator voltage. In this study, shunt compensation is controlled using a capacitor. To examine the efficacy of the proposed approach, two benchmark models of power systems (57 bus, 118 bus) are utilized. The optimization process is implemented using a graphics processing unit (GPU) to accelerate computation. The effectiveness of the IT2FPSODE was evaluated against several established optimization techniques from previous studies to validate its superiority and consistency. The results demonstrate that the proposed technique could lead to a notable reduction in active power loss, with a decrease of 13.82% in the 57-bus power system and 11.39% in the 118-bus power system.