Increasing Power and Energy in Amonix CPV Solar Power Plants

Kinsey, Geoffrey S.; Nayak, Ajit Kumar; Liu, Mingguo; Garboushian, Vahan

doi:10.1109/jphotov.2011.2172775

Cited by 28 publications

(12 citation statements)

References 6 publications

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“…The most interesting finding is that the Correlation Coefficients (R [4,35,36], but this is the first proposal for a prediction method without the direct measurement of the DNI.…”

Section: Discussionmentioning

confidence: 94%

Analysis and Prediction of Energy Production in Concentrating Photovoltaic (CPV) Installations

2012

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Abstract:A method for the prediction of Energy Production (EP) in Concentrating Photovoltaic (CPV) installations is examined in this study. It presents a new method that predicts EP by using Global Horizontal Irradiation (GHI) and the Photovoltaic Geographical Information System (PVGIS) database, instead of Direct Normal Irradiation (DNI) data, which are rarely recorded at most locations. EP at four Spanish CPV installations is analyzed: two are based on silicon solar cells and the other two on multi-junction III-V solar cells. The real EP is compared with the predicted EP. Two methods for EP prediction are presented. In the first preliminary method, a monthly Performance Ratio (PR) is used as an arbitrary constant value (75%) and an estimation of the DNI. The DNI estimation is obtained from GHI measurements and the PVGIS database. In the second method, a lineal model is proposed for the first time in this paper to obtain the predicted EP from the estimated DNI. This lineal model is the regression line that correlates the real monthly EP and the estimated DNI in 2009. This new method implies that the monthly PR is variable. Using the new method, the difference between the predicted and the real EP values is less than 2% for the annual EP and is in the range of 5.6%-16.1% for the monthly EP. The method that uses the variable monthly PR allows the prediction of the EP with reasonable accuracy. It is therefore possible to predict the CPV EP for any location, using only widely available GHI data and the PVGIS database. OPEN ACCESSEnergies 2011, 4 771

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“…The most interesting finding is that the Correlation Coefficients (R [4,35,36], but this is the first proposal for a prediction method without the direct measurement of the DNI.…”

Section: Discussionmentioning

confidence: 94%

Analysis and Prediction of Energy Production in Concentrating Photovoltaic (CPV) Installations

2012

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“…Solar cells with efficiencies approaching 40% are currently commercially available [1,2]. On the module level, solar power conversion efficiencies above 30% have been reported [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Modeling of concentrating photovoltaic and thermal systems

Helmers

Bett

Parisi

et al. 2012

Progress in Photovoltaics

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An energy balance model for concentrating photovoltaic and thermal (CPVT) systems is presented. In the model, the CPVT system and its environment are represented using a set of input parameters. The main outputs of the model are the system's electrical and thermal efficiencies. The model accounts for optical losses. Thermal losses are derived from a thermal network model of the hybrid receiver. The solar cell performance is modeled as a function of the temperature and the irradiance. The robustness of the model is demonstrated by a sensitivity analysis of all input parameters. The influence of the operating temperature on the electrical and thermal performances and the overall efficiency of the CPVT system are discussed. The limiting cases of maximum electrical and thermal power outputs are presented. Further, the influence of the concentration ratio on the electrical and thermal performance and on the partitioning of these two power outputs is analyzed in detail. It is shown that high concentration reduces the thermal losses considerably and increases the electrical efficiency. At concentration ratios above 300, the system operates with an overall efficiency of 75% at temperatures up to 160°C

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“…As CPV plays a more serious role in the PV market, the spectrum sensitivity issue has garnered more and more attention. Exploring research pertinent to this topic can be found in recent publications by academic institutes and commercial companies . Considering the significant influence of spectrum variation on solar cell efficiency and the limited spectrum data resources, it would be valuable to deploy more R8D activities to quantify spectrum sensitivity.…”

Section: R8d Opportunities For High Efficiency Pvmentioning

confidence: 99%

High efficiency photovoltaics: on the way to becoming a major electricity source

Wang

Byrne

Kurdgelashvili

et al. 2012

WIREs Energy & Environment

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The dramatic growth of the photovoltaic (PV) industry—accelerated by increased economies of scale, technology improvements, research and development efforts, and strong policy support—has pushed PV to set out on its pathway to becoming a major electricity source. The speed and course of this pathway will be determined by the development of PV energy price and its relation to market electricity sales price. The current gap between PV energy price and market electricity sales is often covered by substantial government subsidies. Using the United States PV market as a case study to illustrate the need for PV energy price decline, this article details the potential contribution of high‐efficiency PV based on different materials to realize such a decline and a substantial PV electricity share. It is found that—with considerable government support—PV's electricity share in the United States can rise to 25% by 2050. In order to help the PV industry achieve significant progress without large government subsidies, more radical decline of PV system cost is necessary. As such, quantitative analysis is deployed to investigate the value of module efficiency in lowering the total PV electricity cost through a levelized cost of energy analysis. Next, the article investigates in detail the research and development opportunities for high‐efficiency PV and projects the required efficiency‐price ranges for different types of PV modules. This article is categorized under: Photovoltaics > Economics and Policy

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Increasing Power and Energy in Amonix CPV Solar Power Plants

Cited by 28 publications

References 6 publications

Analysis and Prediction of Energy Production in Concentrating Photovoltaic (CPV) Installations

Analysis and Prediction of Energy Production in Concentrating Photovoltaic (CPV) Installations

Modeling of concentrating photovoltaic and thermal systems

High efficiency photovoltaics: on the way to becoming a major electricity source

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