Widi Aribowo, Reza Rahmadian, Mahendra Widyartono, Ayusta Lukita Wardani, Bambang Suprianto, Supari Muslim
The Chimp Optimization Algorithm (ChOA) is a new metaheuristic method based on the life and colony of chimps in nature. A chimp can have an infinite number of colonies and tasks. Each individual has a task that leads to the colony's goal, which is to find prey. This study will propose applying the chimp optimization algorithm used to improve the neural network's performance, which is used to tune the power system stabilizers (PSS). Tests were carried out by using a single machine. In this study, the neural network used is a feedforward backpropagation neural network. Measuring the performance of the proposed method is to compare it with other methods. From the experiment, the proposed method can reduce the average overshoot and undershoot velocity values by 12.75% and 31.49%, respectively. The results showed that the proposed method, namely ChOA-FFBNN, has the best performance and is adaptive. © 2021 IEEE.
Universitas Negeri Surabaya, Department of Electrical Engineering, Surabaya, Indonesia
