非均匀温度分布下温差发电系统的多峰值寻优

Multi-peak optimization strategy for thermoelectric power generation system under non-uniform temperature distribution

在温度非均匀分布的场景下,集中式的半导体温差发电片(TEG)系统会出现多个最大功率点,如何从多个最大功率点中找到一个全局最大的最大功率点就变得尤为重要。提出了一种新型的交互式优化算法(GSA-ACS),用于实现热电片发电系统的最大功率追踪。该算法混合了自适应罗盘算法(ACS)和万有引力搜素算法(GSA),分别从恒定温度的场景、温度非均匀分布的场景、变化温度的场景,与扰动观察法(P&O)、均衡优化算法(EO)、ACS、GSA相比较,GSA-ACS能以更快的速度和更高的质量达到全局的最大功率点。

In the case of non-uniform temperature distribution,there will be multiple maximum power points in the centralized TEG system.How to effectively find a global maximum maximum power point from multiple maximum power points becomes particularly important.A novel interactive optimization algorithm(GSA-ACS)for maximum power tracking of thermoelectric sheet power generation systems was proposesed.The algorithm mixed the Adaptive Compass Algorithm(ACS)and the Gravitational Search Algorithm(GSA)respectively from the scene of constant temperature,the scene of non-uniform temperature distribution,the scene of changing temperature,and the perturbation and observation method(P&O),balanced optimization algorithm(EO),Adaptive Compass Algorithm(ACS),and Gravitational Search Algorithm(GSA),GSA-ACS could reach the global maximum power point at a faster speed and with higher quality.