Exergetic characterization of flat plate solar collector using genetic algorithm

With the rapid advancement of technology, the global demand for energy is increasing exponentially. It is crucial to focus on energy conservation and conversion across all sectors. This study conducted a second law or exergy analysis on a solar water heating system to uncover hidden losses during the process. To optimize exergetic efficiency, a genetic algorithm was employed to control the overall loss coefficient of a solar flat plate collector. Four decision variables were used in the genetic algorithm—heat flux rate, glass cover temperatures at the inlet and exit, and collector plate temperature to minimize the overall loss coefficient. Energy efficiency, entropy generation, and exergy destruction were estimated for various mass flow rates using thermodynamic equilibrium equations. Exergy correlations were developed concerning mass flow rate (0.001–0.009 kg/s), inlet temperature (300 K–360 K), collector plate area (1–10 m²), incident solar energy (400–900 W/m²), optical efficiency (0.4%–1%), and ambient temperature (300–315 K) under a range of initial conditions. It was found that exergy efficiency slightly increased (0.01%–0.08%) over a 12-h period. Although this increase is small, it can significantly contribute to energy conservation over the long term. The genetic algorithm predicted the minimum loss coefficient occurring during peak hours (12–14 p.m.) with respect to four decision variables. The results of this study were compared with existing literature and showed good agreement. In addition to the exergy analysis, an uncertainty error analysis was performed to assess the reliability and accuracy of the experimental measurements and computational predictions. By quantifying these uncertainties, the study ensured that the reported enhancements in exergy efficiency and the optimization results obtained through the genetic algorithm are robust and credible. This rigorous error analysis adds confidence to the findings, highlighting the potential for improved energy conservation in solar water heating systems.

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Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
Published
2024-10-07
DOI
https://doi.org/10.1177/09544089241282135
Citations
2
Primary Topic
Solar Thermal and Photovoltaic Systems
Type
article
Field-Weighted Citation Impact
0.20
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article

Exergetic characterization of flat plate solar collector using genetic algorithm

P. Krishnakumar, Sathyakala Ponnusamy, Balaji Kalaiarasu, Sai Sundara Krishnan Gangadharan
2 citations
Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
Solar Thermal and Photovoltaic Systems
0.20
article

Exergetic characterization of flat plate solar collector using genetic algorithm

P. Krishnakumar, Sathyakala Ponnusamy, Balaji Kalaiarasu, Sai Sundara Krishnan Gangadharan
article en
2 citations

Abstract

With the rapid advancement of technology, the global demand for energy is increasing exponentially. It is crucial to focus on energy conservation and conversion across all sectors. This study conducted a second law or exergy analysis on a solar water heating system to uncover hidden losses during the process. To optimize exergetic efficiency, a genetic algorithm was employed to control the overall loss coefficient of a solar flat plate collector. Four decision variables were used in the genetic algorithm—heat flux rate, glass cover temperatures at the inlet and exit, and collector plate temperature to minimize the overall loss coefficient. Energy efficiency, entropy generation, and exergy destruction were estimated for various mass flow rates using thermodynamic equilibrium equations. Exergy correlations were developed concerning mass flow rate (0.001–0.009 kg/s), inlet temperature (300 K–360 K), collector plate area (1–10 m²), incident solar energy (400–900 W/m²), optical efficiency (0.4%–1%), and ambient temperature (300–315 K) under a range of initial conditions. It was found that exergy efficiency slightly increased (0.01%–0.08%) over a 12-h period. Although this increase is small, it can significantly contribute to energy conservation over the long term. The genetic algorithm predicted the minimum loss coefficient occurring during peak hours (12–14 p.m.) with respect to four decision variables. The results of this study were compared with existing literature and showed good agreement. In addition to the exergy analysis, an uncertainty error analysis was performed to assess the reliability and accuracy of the experimental measurements and computational predictions. By quantifying these uncertainties, the study ensured that the reported enhancements in exergy efficiency and the optimization results obtained through the genetic algorithm are robust and credible. This rigorous error analysis adds confidence to the findings, highlighting the potential for improved energy conservation in solar water heating systems.

Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering
PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH (IN), Amrita Vishwa Vidyapeetham (IN)
Affordable and clean energy
Openalex Percentile: Top 58%
Solar Thermal and Photovoltaic Systems
0.20
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