Optimizing AGC in Implantable Devices: Predictive PID Plus Square Root Derivatives Algorithm

Abstract

This study introduces an advanced algorithm for optimizing automatic generation control (AGC) in implantable devices, addressing the challenges posed by the variability of renewable energy sources such as solar and wind power. The proposed approach utilizes a predictive proportional-integral-derivative (PID) controller enhanced with square root derivatives, specifically designed for power systems with high photovoltaic and wind penetration. This innovative method aims to mitigate the instability caused by the fluctuating nature of renewable energy sources. The research develops a framework that models the electricity network dynamics, incorporating high levels of solar (PV) and wind energy. The introduction of a 'Kindly Please' regulator is a novel aspect of this study, designed to augment system stability amidst increasing reliance on renewable resources. This regulator is integrated into the simulation environment, allowing for the prediction and optimization of AGC performance based on various output scenarios.