Exploring the Effectiveness of Different MPPT Algorithms for Thermoelectric Generator Optimization: A Comparative Study

Thermoelectric Generator (TEG) is an essential semiconductor gadget that give rise to electrical current for voltage devices by converting heat flow and the hotness difference between two edges of the Thermoelectric Generator device. Conventionally, a Thermoelectric Generator is useful for small power utilization. When the electrical load matches with the inner resistance of the Thermoelectric Generator, it generates topmost power. However, coordination with impedance cannot be sure in every circumstance. As a consequence, Thermoelectric Generator (TEG) serve at lesser efficiency. Due to these consequences, different maximum power point tracking (MPPT) algorithms are practiced. In this suggested task we modeled the Thermoelectric Generator (TEG) system and simulated the system with two different MPPT algorithms. This task mainly highlights the making use of waste heat generated from various spots like automotive exhaust, bakehouse, kitchen oven, pastry shop, hot water pipes, solar photovoltaic (PV) panels, body heats, etc. which commonly is not taken into deliberation. The proposed model is combined with three different parts of constituent particularly the thermoelectric Generator (TEG), charge controller and load. The entire specimen has been authenticated through MATLAB Simulinkbased software results. The topmost power from the TEG is acquired actively by perturb and observe ( P&O) and variable fractional order Fuzzy logic (VFOLC) maximum power point tracking (MPPT) algorithms.