Optimal Deployment of DG and D-STATCOM using Moth Flame Optimization Algorithm in Radial Distribution System

A recent nature-inspired metaheuristic swarm intelligence algorithm called Moth Flame Optimization (MFO) is proposed for Renewable Distributed Generation (RDG) and Distribution Static Compensator (D-STATCOM) optimal siting and sizing problem. First, a power flow analysis was performed which form the base case scenario. Then, the MFO is integrated with the power flow method to implement DG and combine DG/DSTATCOM in the IEEE 33-bus radial distribution system. A multi-objective function was formulated for use in the MFO to minimize total power losses and improve the voltage profile of the system subject to the network constraints. The effectiveness of the proposed MFO is tested, its performance investigated and compared with two swarm-based algorithms, namely; Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) algorithm. The results of the simulation showed that MFO can optimally site and size DG and DSTATCOM in a radial distribution system effectively, thus reducing the total power losses and improving the system's voltage profile compared to its equivalents PSO. The effectiveness of the proposed MFO is very fast in the optimization process, thus reducing the computational time and minimizing computer resources usage over FA and PSO. Also, the simulation results revealed combine DG/DSTATCOM provides better voltage profile enhancement and reduces the active power loss by 72% compared to the DG system only with 49.7% loss reduction.