Particle Swarm (PSO) and Bacterial Foraging (BF) Optimizers are two widely used optimization
techniques. A proper combination of these two algorithms would improve their search
capability while minimizing their shortcomings, such as parameter dependency and premature convergence.
This paper presents a hybrid optimization algorithm that combines PSO and BF
(HPSBF) to ensure security and the system’s stability following faults and disturbances. The formulated
objective function is claimed to be innovative and straightforward.
The set objectives are to minimize the dropped load by shedding relays while maximizing the lowermost
swing frequency. The optimal operation of Under-Frequency Load-Shedding (UFLS)
Relays is driven by the HPSBF technique as a bounded optimization with bounds representing
the limits of the system’s state variables. The viability of the HPSBF is verified against
conventional-, PSO-, and BF-UFLS approaches. The standard IEEE 9-bus and IEEE 39-bus systems
are exploited to examine the response of the developed UFLS techniques. The tested systems
are exposed to various operational scenarios such as loss of power plants and a considerable abrupt
load increase. The DigSilent power factor software is used to simulate the IEEE 9- and 39-bus systems,
while MATLAB code was implemented to obtain optimal operational points for the implemented
algorithms. The HPSBF accomplished the uppermost swing frequency and the
lowermost quantity of the disconnected load. Furthermore, the computational times of HPSBF
are equivalent to those of the PSO.