Multi-Objective Optimization Research Based on NSGA-II and Experimental Study of Triplex-Tube Phase Change Thermal Energy Storage System

Yi Zhang, Haoran Yu, Yingzhen Hou and Neng Zhu ()
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Yi Zhang: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
Haoran Yu: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
Yingzhen Hou: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
Neng Zhu: School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China

Energies, 2025, vol. 18, issue 8, 1-27

Abstract: Energy storage technology is crucial for promoting the replacement of traditional energy with renewable energy and regulating the energy supply–demand relationship. This paper investigates a triplex-tube thermal energy unit storage to solve the intermediate heat storage and heat transfer problem of hot water supply and demand in clean heating systems. A multi-objective optimization method based on the elitist non-dominated sorting genetic algorithm (NSGA-II) was utilized to optimize the geometric dimensions (inner tube radius r 1 , casing tube radius r 2 , and outer tube radius r 3 ), focusing on heat transfer efficiency ( ε ), heat storage rate ( P t ), and mass ( M ). On this basis, the influence of the optimization variables was analyzed. The optimized configuration ( r 1 = 0.014 m, r 2 = 0.041 m, and r 3 = 0.052 m) was integrated into a modular design, achieving a 2.12% improvement in heat transfer efficiency and a 73.23% increase in heat storage rate. Experimental results revealed that higher heat transfer fluid (HTF) temperatures significantly reduce heat storage time, while HTF flow rate has a minimal impact. Increasing the heat release temperature extends the phase change material (PCM) heat release duration, with the flow rate showing negligible effects. The system’s thermal supply capacity is susceptible to heat release temperature.

Keywords: triplex-tube thermal energy storage; multi-objective optimization; phase change integrated module; heating capacity response (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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