Abstract
This study attempts to develop a grey wolf optimizer (GWO) based maximum power point tracking (MPPT) control of centralized thermoelectric generator (TEG) applied in thermal power stations under non-uniform temperature distribution (NTD) condition. Since only one converter is employed in centralized TEG systems, the total costs of implementation and maintenance is minimal among different structures. Nevertheless, numerous maximum power points (MPPs) often emerge under NTD condition, in which conventional MPPT techniques might be easily trapped at multiple local MPPs (LMPPs) thus the overall efficiency is inevitably low. In order to effectively search the global MPP (GMPP), GWO is proposed in this paper, which can achieve an appropriate balance between the exploration and exploitation under NTD condition. In contrast with perturb and observe (P&O) and particle swarm optimization (PSO), two case studies, namely, start-up test and step change of temperature, are employed to prove the efficiencies and benefits of GWO, respectively.
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