基于人工蜂群算法的温差发电阵列最优重构方法

doi:10.16183/j.cnki.jsjtu.2022.284

摘要/Abstract

摘要：

在新能源发电技术快速发展的背景下,温差发电(TEG)技术能够很好地利用新能源发电中产生的废热.然而,温度分布的变化会使得TEG阵列的输出特性恶化、发电效率降低.提出基于人工蜂群(ABC)算法的TEG阵列重构方法,在3种不同温度分布情况下,利用ABC在对称9×9和不对称10×15两种TEG阵列进行动态重构.将所提算法与遗传算法、粒子群优化算法和秃鹰搜索优化算法3种启发式算法作对比,并给出由ABC重构后的TEG阵列温度分布图.结果表明:ABC能够提高TEG阵列的输出功率,输出功率-电压曲线均趋向呈现出单个峰值.此外,利用基于RTLAB平台上的硬件在环实验验证了硬件可行性.

关键词: 温差发电, 人工蜂群算法, 动态重构, 硬件在环实验

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.

Key words: thermoelectric generation, artificial bee colony algorithm (ABC), dynamic reconfiguration, hardware-in-the-loop (HIL)

中图分类号:

TM913

杨博, 胡袁炜骥, 郭正勋, 束洪春, 曹璞璘, 李子林. 基于人工蜂群算法的温差发电阵列最优重构方法[J]. 上海交通大学学报, 2024, 58(1): 111-126.

YANG Bo, HU Yuanweiji, GUO Zhengxun, SHU Hongchun, CAO Pulin, LI Zilin. Optimal Reconfiguration Method for Thermoelectric Power Array Based on Artificial Bee Colony Algorithm[J]. Journal of Shanghai Jiao Tong University, 2024, 58(1): 111-126.

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算法	算例结果	不均匀温度分布类型
算法	算例结果	对角线	外部	内部
未优化状态	P_max/W	532.4	670.9	519.8
ABC	P_max/W	585.8	694.4	533.2
	P_ave/W	579.0	693.7	533.1
GA	P_max/W	585.8	694.4	533.2
	P_ave/W	565.5	694.4	532.8
PSO	P_max/W	585.8	686.9	533.2
	P_ave/W	570.4	675.1	532.8
BES	P_max/W	565.0	647.0	532.6
	P_ave/W	558.7	623.3	532.4

算法	运行时间/s
算法	对角线	外部	内部
ABC	6.26	6.36	6.39
GA	6.39	6.28	6.26
PSO	12.41	12.35	12.97
BES	15.96	15.66	15.00

算法	算例结果	不均匀温度分布类型
算法	算例结果	对角线	外部	内部
未优化状态	P_max/W	1048.5	1143.8	1017.5
ABC	P_max/W	1191.2	1193.3	1036.9
	P_ave/W	1161.4	1192.4	1036.8
GA	P_max/W	1162.3	1193.4	1036.9
	P_ave/W	1130.1	1192.0	1036.7
PSO	P_max/W	1156.6	1193.0	1036.8
	P_ave/W	1133.0	1180.3	1036.5
BES	P_max/W	1103.5	1155.5	1036.1
	P_ave/W	1091.2	1150.9	1035.8

算法	运行时间/s
算法	对角线	外部	内部
ABC	7.82	7.79	7.82
GA	7.59	7.20	7.42
PSO	18.48	18.45	18.47
BES	16.41	16.67	16.78