DocumentCode
42542
Title
A Combination of Concentrator Photovoltaics and Water Cooling System to Improve Solar Energy Utilization
Author
Ming-Tse Kuo ; Wen-Yi Lo
Author_Institution
Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Volume
50
Issue
4
fYear
2014
fDate
July-Aug. 2014
Firstpage
2818
Lastpage
2827
Abstract
In this paper, concentrator photovoltaics (CPVs) were used to integrate the extraction of light energy and thermal energy. The water cooling system that is proposed in this paper provides effective cooling by circulating cold water to remove heat in the photovoltaics. The experimental results were subsequently analyzed and compared with the power generation efficiency of the examined photovoltaics. The use of a water-circulation cooling system improves the power capacity of the photovoltaics by 2%-15% and enhances the power generation efficiency of the photovoltaics by 2.29%-3.37%. Through the combined application of photovoltaic and thermal technologies, the total energy of the overall system can be improved by 37%-59% even after accounting for the energy consumption of the cooling system. As a result, environmental protection, energy savings, and an increase in the efficiency of sunlight utilization can be achieved. Finally, a neural network was used to optimize this increase in efficiency.
Keywords
cooling; energy consumption; solar cells; solar energy concentrators; CPVs; circulating cold water; concentrator photovoltaics; efficiency 2.29 percent to 3.37 percent; energy consumption; energy savings; environmental protection; light energy extraction; neural network; power capacity; power generation efficiency; solar energy utilization; sunlight utilization efficiency; thermal energy; thermal technologies; water-circulation cooling system; Cooling; Photovoltaic systems; Temperature distribution; Temperature measurement; Temperature sensors; Water heating; Neural network applications; Neural-network applications; Photovoltaic cells; Prediction methods; Solar energy; Water heating; photovoltaic cells; prediction methods; solar energy; water heating;
fLanguage
English
Journal_Title
Industry Applications, IEEE Transactions on
Publisher
ieee
ISSN
0093-9994
Type
jour
DOI
10.1109/TIA.2013.2296656
Filename
6697849
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