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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Solar Energyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Solar Energy
Article . 2018 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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In-situ prediction of focal flux distribution for concentrating photovoltaic (CPV) system using inverse heat transfer technique for effective design of receiver

Authors: S. Somasundharam; K.S. Reddy; N. Premjit Singh;

In-situ prediction of focal flux distribution for concentrating photovoltaic (CPV) system using inverse heat transfer technique for effective design of receiver

Abstract

Abstract The knowledge of heat flux distribution on the receiver area is very important to improve the overall performance of the solar Concentrating Photovoltaic (CPV) system. In a CPV system, non-uniform flux distribution is one of the common issues. Non-uniform illumination of heat flux is mainly due to the limitations in the design of concentrator optics, slope error in the concentrator profile, tracking system error, misalignment of concentrator, and the efficiency of refractive lens/reflecting mirrors. The prediction of the heat flux distribution will play a vital role in the CPV system such as designing the receiver area, selection of the materials, thermal management and to estimate the power output. In this paper, an experimental work for in-situ prediction of heat flux distribution profile on a flat plate receiver is presented. Inverse heat transfer technique is adopted to predict the heat flux distribution. A Gaussian distribution is assumed to model the distribution of the heat flux. The forward problem is a 3-D steady state heat conduction equation subjected to convection and radiation heat loss boundary conditions. The forward problem is solved using Finite Element Method in Ansys APDL. The unknown parameters of the assumed heat flux distribution are then estimated by minimizing the sum of squared error between measured and simulated temperature distribution. A deterministic search technique, Levenberg-Marquardt algorithm is used to solve the inverse problem. The simulated temperature distribution with the predicted heat flux are in good agreement with the measured temperature with a maximum residue of ±5 °C. Also, the deviation between theoretical and predicted total solar energy is found to be

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    citations
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    12
    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).
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    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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Found an issue? Give us feedback
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!
12
Top 10%
Average
Top 10%