Actual PV module performance including spectral losses in the UK
Dept. of Electron. & Electr. Eng., Loughborough Univ., UK
DOI: 10.1109/PVSC.2005.1488452 Conference: Photovoltaic Specialists Conference, 2005. Conference Record of the Thirty-first IEEE
STC efficiencies are not sufficient to compare photovoltaic devices of different semiconductor material or device configurations. The energy yield changes as the variables of STC deviates from their original values when the modules are placed in various climatic conditions. The magnitude of this change for different modules is not always clear and needs to be investigated and modelled. A modeling and analysis method named site specific conditions (SSC) is demonstrated which is a measure-correlate-predict approach. It allows an accurate estimation of the actual energy yield for different sites based on the measurements at one single site. The method takes into account the effect of the physical operating environment and translates this to other meteorological conditions on the basis of physics related formulae. Our results show a large seasonal variation for modules for the different effects. For crystalline modules losses of up to 12% in the summer is due to the temperature effect while the multi-junction thin film losses of more than 30% in the winter is due to spectral changes and incidence angle effect for the UK.
Available from: George Elias Georghiou
- "More specifically, a fundamental mathematical model used to predict the power produced by a PV system is the single-point efficiency model  which requires only the irradiance on the plane of array (POA), G POA , the area of the PV array, A, and the efficiency at standard test conditions (STC), η STC , of irradiance 1000 W/m 2 , cell temperature of 25 °C and air mass (AM) 1.5. The simplicity of this model's input parameters is compromised by the fact that it cannot sufficiently account for the deviations in efficiency associated with the different PV technologies and the climatic conditions of the place of operation . In order to optimize the prediction accuracy more elaborate models which include up to thirty different parameters have been developed in an attempt to fully model PV performance and account for factors such as temperature, angle of incidence (AOI), spectrum, mismatches, cable losses etc . "
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ABSTRACT: Mathematical, empirical, and electrical models have long been implemented and used to predict the energy yield of many photovoltaic (PV) technologies. The purpose of this paper is to compare the annual DC energy yield prediction errors of four models namely the single-point efficiency, single-point efficiency with temperature correction, the Photovoltaic for Utility-Scale Applications (PVUSA), and the one-diode model, against outdoor measurements for different grid-connected PV systems in Cyprus over a 4-year evaluation period. The different models showed a wide variation of prediction errors, demonstrating a strong dependence between model performance and the different technologies. In particular, it was clearly shown that the application of temperature loss correction based on the manufacturer's temperature coefficients of power at maximum power point assisted in improving the energy yield prediction significantly especially for the crystalline silicon (c-Si) technologies. In most cases, the best agreement between the modeled results and outdoor-measured annual DC energy yield for mono-crystalline silicon (mono-c-Si) and multi-crystalline silicon (multi-c-Si) technologies was obtained using the one-diode model. The energy yield for the thin-film technologies was more accurately predicted using the PVUSA model with the exception of the copper-indium-gallium-diselenide (CIGS) technology, which was best predicted using the single-point efficiency with temperature correction and one-diode models, thus demonstrating similar physical properties to c-Si technologies. The paper further quantifies the combined uncertainties associated with the predicted energy yield as a function of the input parameters for the single-point efficiency, single-point efficiency with temperature correction, and the PVUSA models. Copyright © 2011 John Wiley & Sons, Ltd.
Available from: Jayanta Deb Mondol
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ABSTRACT: The performance of a roof mounted grid-connected photovoltaic (PV) system in Northern Ireland was monitored over 3 years on annual, seasonal and monthly bases. The overall system performance was adversely affected by low insolation conditions; 19% of total incident insolation was absorbed at irradiance level below 200 W/m2 and 67% below 600 W/m2, only 6·2% above 900 W/m2. In summer and winter, the PV and system efficiencies were 9·0 and 8·5%, and 7·8 and 7·5%, respectively and inverter efficiencies were 86·8 and 85·8%, respectively. The inverter for this particular system was oversized; 77% of the total DC energy produced when inverter's operating load was 50% of its rated capacity. The annual average monthly system performance ratio (PR) was 0·61 with seasonal variation 0·59 to 0·63. The average monthly PV, system and inverter efficiencies over the whole monitored period were 8·8, 7·6 and 86·8%, respectively. The main losses of the system were inverter DC/AC conversion loss, inverter threshold loss and low insolation loss. Copyright © 2007 John Wiley & Sons, Ltd.
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ABSTRACT: Presented is a method for calculating the power-productivity of photovoltaic (PV) installations with sunlight concentrators and multijunction (MJ) solar cells (SC) allowing for variation of their power efficiency in dependence on real operation conditions - spectral composition and sunlight flux density and also on temperature of multijunction cells. The yearly totals of specific electric power generated by a module at constant and variable efficiency values have been calculated. It has been shown that allowing for the joint effect of the sunlight characteristics and multijunction SC temperature on the photovoltaic module efficiency must be realized in simulating the module operation in any power generating systems. These allows excluding the overestimations of the yearly power totals generated by a solar installation in determining the power productivity.
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