Voltage and frequency regulation in smart grids via a unique Fuzzy PIDD2 controller optimized by Gradient-Based Optimization algorithm

This paper proposes a maiden intelligent controller design that consists of a Fuzzy Proportional- Integral-Derivative-Double Derivative (FPIDD2) controller whose parameters are fine-tuned using the Gradient-Based Optimization algorithm (GBO). The proposed FPIDD2 regulator is employed as a secondary regulator for stabilizing the combined voltage and frequency loops in a two-area interconnected power system. It has been shown that the GBO optimization algorithm outperforms other optimization strategies such as the Chimp Optimization Algorithm (ChOA), the Whale Optimization Algorithm (WOA), and the Gorilla Troops Optimization algorithm (GTO). The proposed FPIDD2 controller is tested in a conventional two-area power system. Then, the investigation is expanded to a two-area hybrid system, with each area comprising a mix of traditional (thermal, gas, and hydraulic power plants) and renewable generation units (wind and solar power). Additionally, the proposed controller takes into account system nonlinearities (such as generation rate limitations, governor deadband, and communication time delays), system uncertainties, and load/renewables fluctuations. In the two tested systems, the dynamic responses of each system demonstrate that FPIDD2 has a superior ability to attenuate the deviations in voltage and frequency in both areas of the system. In the studied conventional system, the proposed FPIDD2 controller is compared with a PID controller tuned by the Multi-Objective Non-Linear Threshold Accepting Algorithm (MONLTA), which has been presented in the literature, and a Fuzzy PID (FPID) controller tuned by GBO. In the investigated hybrid system, the suggested FPIDD2 regulator is compared to a GBO-tuned Integral Derivative-Tilted (ID-T) controller and FPID controller. As a fitness function (FF) for the GBO, the criteria of minimizing the integral time absolute error (ITAE) are applied. The results are presented in the form of MATLAB/SIMULINK time-domain simulations.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).