Optimal Design and Performance Analysis of Thermoelectric Power Generation Device Based on Multi‐Objective Genetic Algorithm. Issue 6 (28th April 2021)

• Record Type: Journal Article
• Authors: Wu, Jinmeng; Chen, Yan; Dou, Yinke; Ma, Chunyan; Du, Qian; Liu, Qiang
• Is Part Of: Advanced theory and simulations. Volume 4:Issue 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-04-28
• Subjects: multi‐objective genetic algorithms -- power generation characteristics -- thermoelectric generators -- waste heat; Science -- Simulation methods -- Periodicals; Science -- Methodology -- Periodicals; Engineering -- Simulation methods -- Periodicals; Engineering -- Methodology -- Periodicals; 507.21
• DOI: 10.1002/adts.202000271
• Languages: English
• ISSNs: 2513-0390

Abstract

Abstract: The combined use of flue gas waste heat resources and thermoelectric generators (TEGs) is considered to be a relatively reliable method to generate electricity. The focus of this study is on the optimization and improvement of the hot‐end heat collection pipe. This paper aims to increase the temperature difference between hot and cold ends of TEG and enhance uniformity of temperature distribution, thereby improving the output power of the TEG system. To balance the temperature difference between the cold and hot ends of the TEG, the pressure drop from the inlet to the outlet and the mass of TEG hot end pipes, a finite element simulation model is constructed. Meanwhile, a multi‐objective genetic algorithm is applied to optimize the structure of four dimensions: fin bottom length, fin height, fin thickness, and outlet diameter. Three optimization objectives, namely, average temperature difference, total pressure drop from inlet to outlet, and pipeline mass are globally optimized to determine the best size, based on which the accuracy of the simulation model is verified by conducting experiments. Abstract : The combined use of flue gas waste heat resources and thermoelectric generators is considered to be a relatively reliable method to generate electricity. To increase output power and conversion efficiency, a multi‐objective genetic algorithm is applied to optimize a thermoelectric generator system structure of four dimensions. Through optimized design, a more reasonable structure is obtained.