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首页> 外文期刊>Solar Energy >Application of genetic algorithm with multi-objective function to improve the efficiency of glazed photovoltaic thermal system for New Delhi (India) climatic condition
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Application of genetic algorithm with multi-objective function to improve the efficiency of glazed photovoltaic thermal system for New Delhi (India) climatic condition

机译:多目标函数遗传算法在提高新德里(印度)气候条件下的玻璃光伏热系统效率中的应用

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摘要

The aim of this paper is to investigate an improvement in the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithm (GA) with multi-objective functions for New Delhi, India climatic condition. There are several parameters influencing efficiency of PVT system which inter alia include length and depth of the channel, velocity of air fluid flowing into the channel, thickness of the tedlar and glass, temperature of inlet fluid. All these parameters have been considered to optimize the efficiency of the PVT system. An attempt has also been made to model and optimize the parameters of glazed hybrid single channel PVT module considering the two objective functions separately which are: (i) the overall exergy efficiency (ii) the overall thermal efficiency. Using GA, both of the above objective functions are separately optimized and analyzed for each of the two cases: namely, Case-I: Improvement in exergy and thermal efficiency when overall exergy efficiency is optimized and Case-II: Improvement in exergy and thermal efficiency when overall thermal efficiency is optimized. The variables used in GA are those that could be varied, keeping parameters like solar radiation, ambient temperature unchanged in the algorithmic calculation. The electrical and thermal efficiencies after optimization were found 14.15%, 11.88% and 14.08%, 19.48% respectively. Similarly the overall exergy and thermal efficiency are 14.87% and 56.54% respectively for both the cases. It has been observed that there is improvement in overall exergy efficiency and overall thermal efficiency by 4.6% and 13.14% respectively during the optimization process. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文的目的是借助具有多目标功能的遗传算法(GA),研究针对印度新德里气候条件的光伏热(PVT)系统效率的提高。影响PVT系统效率的几个参数尤其包括通道的长度和深度,流入通道的空气流体的速度,小提琴和玻璃的厚度,进口流体的温度。已考虑所有这些参数以优化PVT系统的效率。还尝试分别考虑两个目标函数来建模和优化玻璃混合单通道PVT模块的参数:(i)总火用效率(ii)总热效率。使用遗传算法,分别针对以下两种情况分别优化和分析了上述两个目标函数:情况一:优化总火用效率时的火用和热效率提高;情况二:改善火用和热效率优化整体热效率。 GA中使用的变量是可以更改的变量,在算法计算中可以保持太阳辐射,环境温度等参数不变。优化后的电效率和热效率分别为14.15%,11.88%和14.08%,19.48%。同样,这两种情况的总火用和热效率分别为14.87%和56.54%。已经观察到,在优化过程中,总火用效率和总热效率分别提高了4.6%和13.14%。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Solar Energy》 |2015年第7期|153-166|共14页
  • 作者单位

    CMS Govt Girls Polytech Daurala, Meerut 250221, Uttar Pradesh, India|SV Subharti Univ, SITE, Meerut, Uttar Pradesh, India;

    Univ Calif Los Angeles, SMERC, Los Angeles, CA 90095 USA|IGNOU, Sch Engn & Technol, New Delhi 110068, India;

    Indian Inst Technol Delhi, New Delhi, India;

    Jagannath Univ, Jaipur, Rajasthan, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Genetic algorithm; PVT; Exergy; Multi objective;

    机译:遗传算法;PVT;火用;多目标;

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