Abstract
Quantifying and predicting electricity production from photovoltaic (PV) systems is based on measured or modeled irradiance data. These solar resource data consist of global horizontal irradiance, global tilted irradiance, direct normal irradiance, and diffuse horizontal irradiance, which are either derived from satellite observations validated against ground-based measurements or directly obtained from ground-based measurements. The ground-based measurements are made using thermopile or photodiode radiometers. For a PV plant, the efficiency of the energy production is verified by comparing measured Output with the modeled production, which is computed using either modeled or measured irradiance data. Thus, plant performance assessments typically include the uncertainty of the Transposition and, in some cases, decomposition of a given irradiance to convert to the appropriate plane-ofarray (POA) irradiance corresponding to the orientation of the PV installation. Additionally, the various types of uncertainty in radiometric measurements or the modeled irradiance and the PV module specifications influence the model results and thereby further increase the uncertainty. An alternative method of assessing the PV system performance has been to use reference cells to measure the “PV resource.” When used to calculate PV performance ratios, there are inherent systematic differences between radiometers and reference cells, such as spectral, directional, temperature, time responses, nonstability, and nonlinearity differences. Reference cells tend to mimic the performance and characteristics of a PV module more closely. In this report, a framework is proposed to develop standards that will better quantify and characterize the use of reference cells for PV resource measurements. The measurement from an appropriate reference cell in the POA correlates closely with the plant performance, reduces the number of modeling steps needed to simulate PV performance, and hence reduces the uncertainties of the comparisons. Because technologically matched reference cells and PV modules respond similarly to each wavelength of light that composes the incident solar radiation, the uncertainty associated with the changing spectral distribution of incident radiation during the day and year can be greatly reduced. This will reduce the overall uncertainty in estimated PV performance. The same can be said for the angle-of-incidence effects because the reference cells are deployed in the same POA as the PV module. At that point, the main sources of uncertainty are in modeling the temperature effect differences between the reference cells and the PV module and accounting for the difference between the short-circuit current monitored by the reference cells and max power point current and voltage at which the PV module operates. These sources of uncertainty are also associated with typical irradiance measurements made by pyranometers and pyrheliometers; however, typical irradiance measurements also include uncertainties associated with the spectral mismatch between thermopile or photodiode pyranometers and the PV module, which are minimized with the use of reference cells. To enhance the use of reference cells for resource assessment, we identify the necessary data, characteristics, and calibration methodologies of reference cells and how to standardize the use of these data and methods. Further, as we develop this framework, the classification of reference cells will be essential to provide guidance for selecting PV reference cells appropriate for a specific application. As we address the calibration and sources of uncertainties of reference cells, classification schemes and expected limits of performance with respect to certain Parameters become important. Moreover, this report discusses possible technical and analytical challenges that might be encountered as these methodologies are developed. The development of these methodologies is also needed for other initiatives, such as the use of reference cell measurements directly in performance or economic models. It should be possible to meet various application needs with reference cells through the verification, acceptance, and implementation of reference cells for resource assessments.
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