Optimized Fractional Maximum Power Point Tracking Using Bald Eagle Search for Thermoelectric Generation System

Abstract

The amount of energy that a thermoelectric generator (TEG) is capable of harvesting mainly depends on the temperature difference between the hot and cold sides of the TEG. To ensure that the TEG operates efficiently under any condition or temperature variation, it is crucial to have a reliable MPPT that keeps the TEG as close as possible to its MPP. Fractional control is usually preferred over integer control because it allows for more precise, flexible, and robust control over a system. The controller parameters in fractional control are not limited to integer values, but rather can have fractional values, which enables more precise control of the system’s dynamics. In this paper, an optimized fractional PID-based MPPT that effectively addresses two primary issues, dynamic response and oscillation around MPP, is proposed. Firstly, the five unknown parameters of the optimized fractional PID-based MPPT were estimated by the BES “bald eagle search” algorithm. To validate the superiority of the BES, the results were compared with those obtained using other optimization algorithms, such as ant lion optimizer (ALO), equilibrium optimizer (EO), cuckoo search (CS), and WOA “whale optimization algorithm”. The results demonstrate that BES outperforms ALO, EO, CS, and WOA. Additionally, the tracking performance of proposed MPPT was evaluated using two scenarios that involved variations in temperature differences and sudden changes in the load demanded. Overall, the proposed optimized fractional PID-based MPPT effectively improves dynamic performance and eliminates oscillation around MPP under steady state compared to other tracking methods, such as P&O “perturb and observe” and incremental conductance (INR).