Experimental evaluation of a prototype hybrid CPV/T system utilizing a nanoparticle fluid absorber at elevated temperatures

Otanicar, Todd; Dale, J.R.; Orosz, Matthew; Brekke, Nick; DeJarnette, Drew; Tunkara, Ebrima; Roberts, Kenneth P.; Harikumar, Parameswar

doi:10.1016/j.apenergy.2018.07.055

Cited by 95 publications

(20 citation statements)

References 28 publications

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“…1 , remains a challenge, with various studies reporting different optimum filters even for the same PV cell. The optimal wavelengths for Si cells in SSPVT collectors were reported as 751–1126 nm in Taylor et al 25 , 732–1067 nm in Crisostomo et al 29 , 640–1127 nm in Bierman et al 30 , 600–1150 nm in Otanicar et al 31 , 400–1100 nm in Shou et al 32 , and 300–1100 nm in Soule et al 19 . This widespread reveals a lack of consensus in the literature concerning the definition of the optimal filter, even for the most common solar cell.…”

Section: Introductionmentioning

confidence: 97%

Efficiency limits of concentrating spectral-splitting hybrid photovoltaic-thermal (PV-T) solar collectors and systems

2021

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Spectral splitting is an approach to the design of hybrid photovoltaic-thermal (PVT) collectors that promises significant performance benefits. However, the ultimate efficiency limits, optimal PV cell materials and optical filters of spectral-splitting PVT (SSPVT) collectors remain unclear, with a lack of consensus in the literature. We develop an idealized model of SSPVT collectors and use this to determine their electrical and thermal efficiency limits, and to uncover how these limits can be approached through the selection of optimal PV cell materials and spectral-splitting filters. Assuming that thermal losses can be minimized, the efficiency limit, optimal PV material and optimal filter all depend strongly on a coefficient w, which quantifies the value of the delivered thermal energy relative to that of the generated electricity. The total (electrical plus thermal) efficiency limit of SSPVT collectors increases at higher w and at higher optical concentrations. The optimal spectral-splitting filter is defined by sharp lower- and upper-bound energies; the former always coincides with the bandgap of the cell, whereas the latter decreases at higher w. The total effective efficiency limit of SSPVT collectors is over 20% higher than those of either standalone PV modules or standalone ST collectors when w is in the range from 0.35 to 0.50 and up to 30% higher at w ≈ 0.4. This study provides a method for identifying the efficiency limits of ideal SSPVT collectors and reports these limits, along with guidance for selecting optimal PV materials and spectral-splitting filters under different conditions and in different applications.

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Section: Introductionmentioning

confidence: 97%

Efficiency limits of concentrating spectral-splitting hybrid photovoltaic-thermal (PV-T) solar collectors and systems

2021

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“…Unlike the first hybrid approach, both subsystems are thermally decoupled, resulting in lower operating temperatures for the PV cells, and thus higher PV efficiencies [13][14][15][16]. This last family of compact hybrid sys- [17][18][19] or PV cells [20][21][22], where a fraction of the incoming sunlight is absorbed by the filters, the rest being either reflected to the PV subsystem or to the thermal receiver, depending on the filtering technique.…”

Section: Introductionmentioning

confidence: 99%

A multiphysics model of large-scale compact PV–CSP hybrid plants

et al. 2021

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“…Besides, the heated fluid can be actually used in various applications depending on the form of heat energy (water or air). Many studies throughout the world have been done so far to study the performance of photovoltaic thermal (PVT) collectors by all means of analytical solutions, experimental measurements, and numerical simulations . The aim of analytical solutions is to simplify the process of performance estimation, while experimental studies provide a more realistic approach in view of the environmental and operating conditions.…”

Section: Introductionmentioning

confidence: 99%

Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

et al. 2020

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This research article aims to examine the feasibility of several machine learning techniques to forecast the exergetic performance of a building-integrated photovoltaic-thermal (BIPVT) collector. In this regard, it uses multiple linear regression, multilayer perceptron, radial basis function regressor, sequential minimal optimization improved support vector machine, lazy.IBK, random forest (RF), and random tree approaches. Moreover, it implements the performance evaluation criteria (PEC) to evaluate the system's performance from the perspective of exergy. The use of these approaches serves the identification process to realize the relationship between the input-output parameters of the BIPVT system. The novelty of this work is that it utilizes and compares multiple learning algorithms to predict the PEC of BIPVT through design parameters. Hence, the research considers the parameter (PEC) as the essential output of the BIPVT collector, while the input parameters are the length, width, and depth of the duct, located under the PV modules, as well as the air mass flow rate. The results of the research for the statistical indexes of mean absolute error, root mean square error, relative absolute error (%), and root relative squared error (%) show values of (0.2967, 0.3885, 1.8754, and 1.5237) and (0.4957, 0.8153, 2.9586, and 2.8289), respectively, for the training and testing datasets. While R 2 ranges (0.9997-0.9999) for those datasets. Therefore, to estimate the exergy performance of the BIPVT collector, the RF model is superior to other proposed models. K E Y W O R D SBIPVT, exergetic performance, machine learning, performance evaluation criteria, predictive model

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Experimental evaluation of a prototype hybrid CPV/T system utilizing a nanoparticle fluid absorber at elevated temperatures

Cited by 95 publications

References 28 publications

Efficiency limits of concentrating spectral-splitting hybrid photovoltaic-thermal (PV-T) solar collectors and systems

Efficiency limits of concentrating spectral-splitting hybrid photovoltaic-thermal (PV-T) solar collectors and systems

A multiphysics model of large-scale compact PV–CSP hybrid plants

Machine learning predictive models for optimal design of building‐integrated photovoltaic‐thermal collectors

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