In order to reliably simulate the energy yield of photovoltaic (PV) systems, it is necessary to have an accurate model of how the PV modules perform with respect to irradiance and cell temperature. Building on a previous study that addresses the irradiance dependence, two approaches to fit the temperature dependence of module power in PVsyst have been developed and are applied here to recent multi-irradiance and temperature data for a standard Yingli Solar PV module type. The results demonstrate that it is possible to match the measured irradiance and temperature dependence of PV modules in PVsyst. Improvements in energy yield prediction using the optimized models relative to the PVsyst standard model are considered significant for decisions about project financing.
Photovoltaic (PV) systems using microinverters are becoming increasingly popular in the residential system market, as such systems offer several advantages over PV systems using central inverters. PV modules with integrated microinverters, termed AC modules, are emerging to fill this market space. Existing test procedures and performance models designed for separate DC and AC components are unusable for AC modules because these do not allow ready access to the intermediate DC bus. Sandia National Laboratories' Photovoltaics and Distributed Systems department has developed a set of procedures to test, characterize, and model PV modules with integrated microinverters. The resulting empirical model is able to predict the output AC power of with RMS error of 1-2%. This document describes these procedures and provides the results of model validation efforts.
Dual axis trackers employing azimuth and elevation rotations are common in the field of photovoltaic (PV) energy generation. Accurate sun-tracking algorithms are widely available. However, a steering algorithm has not been available to accurately point the tracker away from the sun such that a vector projection of the sun beam onto the tracker face falls along a desired path relative to the tracker face. We have developed an algorithm which produces the appropriate azimuth and elevation angles for a dual axis tracker when given the sun position, desired angle of incidence, and the desired projection of the sun beam onto the tracker face. Development of this algorithm was inspired by the need to accurately steer a tracker to desired sun-relative positions in order to better characterize the electro-optical properties of PV and CPV modules.
The proper modeling of Photovoltaic(PV) systems is critical for their financing, design, and operation. PV LIB provides a flexible toolbox to perform advanced data analysis and research into the performance modeling and operations of PV assets, and this paper presents the extension of the PV LIB toolbox into the python programming language. PV LIB provides a common repository for the release of published modeling algorithms, and thus can also help to improve the quality and frequency of model validation and inter comparison studies. Overall, the goal of PV LIB is to accelerate the pace of innovation in the PV sector.
We present a method for measuring the series resistance of the PV module, string, or array that does not require measuring a full IV curve or meteorological data. Our method relies only on measurements of open circuit voltage and maximum power voltage and current, which can be readily obtained using standard PV monitoring equipment; measured short circuit current is not required. We validate the technique by adding fixed resistors to a PV circuit and demonstrating that the method can predict the added resistance. Relative prediction accuracy appears highest for smaller changes in resistance, with a systematic underestimation at larger resistances. Series resistance is shown to vary with irradiance levels with random errors below 1.5% standard deviation.
Temperature coefficients for PV modules describe the change with temperature of current, voltage and power. Coefficients are commonly determined by linear regression using measured module output at fixed irradiance and varying temperatures. We compare temperature coefficients determined for the same modules from both outdoor and indoor measurements. We find systematic bias in the temperature coefficients for voltage and power, with values derived from indoor measurements consistently smaller in absolute value than values derived from outdoor testing during which the module temperature is measured as specified in IEC 61853-1. Our work suggests that the bias results from a corresponding bias in the estimated module temperature. However we have not identified an alternative arrangement of a few thermocouples that would result in consistent values for temperature coefficients from either indoor or outdoor measurements.
Sandia and Semprius have partnered to evaluate the operational performance of a 3.5 kW (nominal) R&D system using 40 Semprius modules. Eight months of operational data has been collected and evaluated. Analysis includes determination of Pmp, Imp and Vmp at CSTC conditions, Pmp as a function of DNI, effect of wind speed on module temperature and seasonal variations in performance. As expected, on-sun Pmp and Imp of the installed system were found to be ~10% lower than the values determined from flash testing at CSTC, while Vmp was found to be nearly identical to the results of flash testing. The differences in the flash test and outdoor data are attributed to string mismatch, soiling, seasonal variation in solar spectrum, discrepancy in the cell temperature model, and uncertainty in the power and current reported by the inverter. An apparent limitation to the degree of module cooling that can be expected from wind speed was observed. The system was observed to display seasonal variation in performance, likely due to seasonal variation in spectrum.
