Thermoelectric power generation system intelligent Runge Kutta control: A performance analysis using processor in loop testing

Abstract

As an emerging source of clean electrical power, Thermoelectric generation (TEG) finds its applications in heat removal and electricity generation as an efficient improvement tool for thermal devices utilizing fossil fuels. TEG exhibits low power density and its temperature distribution is usually non-uniform over thermal conductive surfaces. Due to the non-uniformity of heat flow and loose surface contact, non-uniform temperature distribution (NTD) appears on TEG surfaces and the TEG control problem becomes complex, multi-solution, nonlinear, and highly sensitive to operating conditions. The bypass diode activation of TEG systems streamlines the power flow in a string of series-connected modules, generating multiple peak points. Classical techniques fail to address these issues of multiple maxima and lose efficiency. To solve this problem, a novel SI-based optimization algorithm, Runge Kutta Method (RUN), is applied as MPPT control. To gauge the performance of the proposed controller several distinct case studies are used, including varying temperatures gradient, NTD, 24-hour thermal profile stochastic temperature, and experimental verification. Additionally, MPPT rating analysis, economic assessment, and statistical studies are done for comparison with other state-of-the-art control techniques. The minimum tracking and settling times have been improved by RUN to 180 ms. For the additional hardware implementation, the maximum levelized cost of energy (LCOE) is about 0.16 $\frac{\$}{\mathrm{kWh}}\left(\frac{1.07\yen }{\mathrm{kWh}}\right).$ The power tracking efficiency of RUN can be above 99 % with energy harvest improvements of 6.3 %.