Artificial rabbits optimization algorithm based tuning of PID controller parameters for improving voltage profile in AVR system using IoT

Abstract

The power system is mainly affected by transient situations caused by switching heavy loads. The system may become unstable when transient situations occur. The power system should be able to perform continuous operation to maintain its voltage within acceptable limits. To achieve more stability and increase its speed of response, an Automatic Voltage Regulator (AVR) system requires the inclusion of a controller. The AVR system in the generating station uses the PID controller to adjust the abnormal voltage caused by transient conditions. To maintain the nominal voltage level under all the load conditions in the system, a bio-inspired meta-heuristic algorithm called Artificial Rabbit Optimization (ARO) algorithm is proposed to tune the PID controller gain parameters and obtain the optimal gain, thereby the AVR system adjusts the generator terminal voltage to nominal levels. The ARO algorithm inspires natural survival techniques to improve the AVR performance by reducing errors. To maintain a stable voltage profile in a power system, this research mathematically models survival techniques using the Internet of Things (IoT) to obtain an optimal solution. As a result, all devices connected to the power network receive a stable voltage that ensures their voltage reliability. The effectiveness of the proposed algorithm for the AVR system is verified with the MATLAB R2022a model, and the statistics functions are implemented in the module of Pandas, Scipy and mathematical investigations done in Numpy. The proposed ARO algorithm achieves a better voltage profile with less than 12.63% maximum peak overshoot during the system's transient response. The proposed algorithm provides the fastest response and highest stability comparable to other optimisation algorithms.