Hybrid GA-GSO-PSO algorithm for optimal PVDG and DSTATCOM placement and sizing in distribution networks

Adding the photovoltaic distributed generation (PVDG) and distribution static compensators (DSTATCOM) to power distribution networks is an effective technique to improve voltage stability and reduce power losses. This research introduces a new hybrid optimization approach that combines genetic algorithms (GAs), glowworm swarm optimization (GSO), and particle swarm optimization (PSO) to determine the optimal sizes and positions for PVDG and DSTATCOM units in radial distribution networks. The primary goal is to minimize total active power loss (TAPL) and total voltage deviation (TVD), while maintaining voltage stability at its peak. To achieve superior optimization results, the GA-GSO-PSO algorithm is produced. It takes advantage of GA’s power in exploring multiple solutions, GSO’s capacity to search locally, and PSO’s rapid convergence. A technique on IEEE 33- and 69-bus systems is performed and a comparison with other algorithms, namely PSO, GSA, PPSOGSA, and MOEA/D is discussed. The results are found to be outstanding since the active power loss in the 33-bus system is decreased by 94.68%, from 210.98 kW to 11.61 kW. The 69-bus system shows an even greater reduction of 98.11%, with losses reducing from 224.94 kW to 4.25 kW. The minimum bus voltage is also improved further. It increases from 0.9038 p.u to 0.992 p.u in the 33-bus system, and from 0.9092 p.u to 0.9943 p.u in the 69-bus system. At the same time, the total voltage deviation is decreased by up to 94.17%. It has been proven that strategically installing suitably sized PVDG and DSTATCOM units can significantly improve power quality, voltage stability, and network efficiency.