Abstract
Identifying a critical node in the power system network (PSN) is very important for properly operating the Electrical Power System (EPS) since some generators operate close to their operating limits, resulting in the generator's breakdown. Fast voltage stability index (FVSI) and line stability index (Lmn) were employed to identify the critical node, and the line close to the voltage instability was identified in the PSN. Particle swarm optimization (PSO) and pathfinder algorithms (PFA) were the two swarm intelligence metaheuristic algorithms used in this study. PSO has been well used to optimize some optimization problems and has a faster convergence speed. However, it has the disadvantage of stock into local optimal, resulting in an inaccurate/non-optimal result. PFA inspires the collective movement of swarms with a leader/pathfinder, but it has the challenge of decreasing search ability when the dimension of the problem is increasing. A new hybridization method of PSO and PFA, called HPSO-PFA, was proposed in this study to tackle the challenges of PFA and PSO and has the merits of both PSO and PFA. This research aims to use an improved hybrid swarm algorithm to diminish the system's actual/real power loss EPS. The merit of PSO in locating the best region in the search area was combined with PFA that can move the swarm to another location and attain the best position. The best solution of PFA was then combined with the velocity of PSO to get the most prominent solution to obtain the minimum power loss. HPSO-PFA was used to solve the optimal reactive power dispatch (ORPD) problem to diminish the losses on the IEEE 30 and 118 bus systems. For the IEEE 9 test system, FVSI and Lmn identified node eight (8) as the critical node, while one of the lines connecting to it undergoes voltage instability. For IEEE 14 bus system, node 14 was identified as the critical/weakest node, and one of the lines connecting to it undergoes voltage instability. PSO and EPSO reduce the losses to 7.608 MW and 7.543 MW for IEEE 9 bus systems, respectively, from the base case of 9.842 MW. Also, 12.263 MW and 12.253 MW for PSO and EPSO of the IEEE 14 bus system from the base case of 13.775 MW. By comparison, the EPSO gave better results than other techniques reported in the literature.
Furthermore, HPSO-PFA reduces the losses of IEEE 30 and 118 test systems to 16.14262 MW and 107.2913 MW, respectively, from the base case of 17.8984 MW and 132.863 MW. The reduction in percentage for the IEEE 30 bus system was 9.8%, while for the IEEE 118 bus system was 19.25%, suggesting that the proposed HPSO-PFA method demonstrates more satisfactory solutions than other algorithms.
Keywords: HPSO-PFA; Enhanced PSO; Optimum reactive power dispatch; Pathfinder algorithm (PFA), and Power loss minimization.