Multi-step Load Optimization for Thermoelectric Power Generation

Abstract

The thermoelectric generator is an essential device used in the process of thermoelectric power generation. This paper researches the energy optimization problem of thermoelectric generators, and the goal is to maximize total output energy over a duration of time. The Multi-Step Load Optimization (MSLO) method is developed for addressing the problem. In our proposed method, we use Artificial Bee Colony (ABC) algorithm to search for the resistance values of multi-step to find a high-quality resistance sequence swiftly. Next, the encoding scheme and local search operators are developed. Instead of using the simulation model directly, we use the Kriging model as evaluation function of ABC algorithm to speed up the calculation of the evaluation value. Results show that the kriging model has high efficiency and accuracy, and when compared to state-of-art maximum power point tracking (MPPT) algorithms, the MSLO method has better optimization performance.