Dingo optimization algorithm for designing power system stabilizer

Abstract

The dingo optimization algorithm (DOA) adopts the social life of dingo dogs. The dingo is a breed of ancient dog originating from Australia. Dingo hunting strategies such as assault with persecution, flocking, and scavenging behavior became the inspiration for DOA. In this paper, DOA is applied to a power system stabilizer (PSS) to dampen low-frequency oscillations (LFO) in a single-machine infinite bus (SMIB). DOA is used to obtain optimal parameters for PSS. The damping controller is designed for optimal lead-lag control. To obtain the performance of the DOA method, the results were compared with the uncontrolled method, conventional PSS, Whale optimization algorithm (WOA), and grasshopper optimization algorithm (GOA). Simulation using MATLAB with three different operating conditions, namely light load (20%), medium load (50%) and high load (100%). From the simulation using MATLAB with SMIB modeling, it was found that the application of the DOA method on PSS has the ability to reduce the average undershoot value by 28.16% and reduce the average undershoot value to 65.57% compared to the conventional PSS method.

Designing a power system stabilizer using a hybrid algorithm by genetics and bacteria for the multi-machine power system

“…In (7) expresses the sum of the transient area under the speed response of each generator for a specific disturbance (e.g., a three-phase short circuit). However, this tuning criterion increases the probability of trapping the optimization method in local minima.…”