Optimal Reconfiguration Method for Thermoelectric Power Array Based on Artificial Bee Colony Algorithm

Abstract

With the rapid development of new energy generation technology, the thermoelectric generation technology (TEG) can make good use of the waste heat generated in new energy generation. However, the change of temperature distribution will worsen the output characteristics and reduce the power generation efficiency of the TEG system. In this paper, a TEG array reconfiguration method based on the artificial bee colony (ABC) algorithm is proposed. In three different temperature distributions, ABC is used for dynamic reconfiguration of symmetric 9×9 and unsymmetric 10×15 TEG arrays. Three meta-heuristic algorithms, the genetic algorithm, the particle swarm optimization algorithm, and the bald eagle search are compared with the proposed method, and the temperature distribution of the TEG array reconfiguration by ABC is given. The results show that ABC can improve the output power of the TEG array, and the output power-voltage curves tend to show a single peak value. In addition, real-time hardware-in-the-loop (HIL) experiment based on the RTLAB platform is undertaken to verify the implementation feasibility.

Keywords

• thermoelectric generation
• artificial bee colony algorithm (abc)
• dynamic reconfiguration
• hardware-in-the-loop (hil)