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Applied Sciences
Article . 2023 . Peer-reviewed
License: CC BY
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Applied Sciences
Article . 2023
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Selection of a Photovoltaic Panel Cooling Technique Using Multi-Criteria Decision Analysis

Authors: Zakariya Kaneesamkandi; Ateekh Ur Rehman;

Selection of a Photovoltaic Panel Cooling Technique Using Multi-Criteria Decision Analysis

Abstract

Photovoltaic panel performance in terms of its efficiency and durability is severely affected by operating temperature when the temperature is much higher than the nominal operating cell temperature in hot climates. Different cooling methods have been reported over several decades, but photovoltaic panel manufacturers or users are yet to adopt a popular method of panel cooling. This is the main concern of the present work. Potential cooling solutions differ in terms of their criteria for performance evaluation, which are efficiency enhancement, costs, reliability, environmental aspects and ergonomics. Hence, there is a need to identify the optimum cooling method. Eight different cooling methods were identified, and the analysis was made with the multi-criteria analysis tool on the different possible attributes. Two different climate zones with different weight schemes are considered for the evaluation process, and the best to the worst cooling solutions have been identified. Five different scenarios depending on the importance given to each evaluation criterion are analyzed. The best cooling method to the worst cooling method has been arranged under each scenario. When the efficiency of operation was given maximum weight, aluminum fin cooling proved to be the best panel cooling method. When the emission reduction criterion was given maximum weight, thermosiphon cooling was the best cooling option. A comparison of the results indicates that thermosiphon works out to be the best option. The second-best method was found to be forced convection cooling when equal weights were applied and thermosiphon cooling when a 40% weight on efficiency enhancement criteria was applied, which is a more practical weight distribution. Phase change cooling and forced convection cooling had the poorest performance among the different cooling methods for all the weighing scenarios.

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Keywords

Technology, photovoltaic panel cooling, QH301-705.5, T, Physics, QC1-999, multi-criteria decision analysis, Engineering (General). Civil engineering (General), Chemistry, photovoltaic efficiency enhancement, TA1-2040, Biology (General), TOPSIS, QD1-999

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
gold