Scholarlink

<p>This study presents a thermal performance analysis of a parabolic trough collector (PTC) system through the coupling of a detailed thermal model with a genetic algorithm-driven multi-objective optimization framework. The core methodological contribution lies in the simultaneous optimization of thermal efficiency, heat loss, and pumping power, accounting for free-molecular conduction effects in the evacuated annulus. The analysis shows that incidence angle and mirror reflectance significantly govern optical efficiency, while rising fluid temperature drives radiative losses and reduces global efficiency. Higher direct normal irradiance (DNI) consistently improves collector performance. The multi-objective optimization using a genetic algorithm with a population of 1000 over 500 generations, generates a Pareto front that reveals clear trade-offs among the three objectives, with optimal solutions favoring high optical efficiency, mirror reflectance, and receiver absorptance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Thermal performance analysis of parabolic trough collector (PTC) with genetic algorithm-driven multi-objective optimization under free-molecular conduction effects in the evacuated annulus

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月27日

查看全文
  • Abu Raihan Ibna Ali,
  • Tafsirul Hassan,
  • Minhaz Ahmed,
  • Nurul Ahad Akil,
  • Ikbal Kabir

摘要

This study presents a thermal performance analysis of a parabolic trough collector (PTC) system through the coupling of a detailed thermal model with a genetic algorithm-driven multi-objective optimization framework. The core methodological contribution lies in the simultaneous optimization of thermal efficiency, heat loss, and pumping power, accounting for free-molecular conduction effects in the evacuated annulus. The analysis shows that incidence angle and mirror reflectance significantly govern optical efficiency, while rising fluid temperature drives radiative losses and reduces global efficiency. Higher direct normal irradiance (DNI) consistently improves collector performance. The multi-objective optimization using a genetic algorithm with a population of 1000 over 500 generations, generates a Pareto front that reveals clear trade-offs among the three objectives, with optimal solutions favoring high optical efficiency, mirror reflectance, and receiver absorptance.