Publications

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IEEE Standard 1547-2003 conformance of several interconnected microinverters was performed by Sandia National Laboratories (SNL) to determine if there were emergent adverse behaviors of co-located aggregated distributed energy resources. Experiments demonstrated the certification tests could be expanded for multi-manufacturer microinverter interoperability. Evaluations determined the microinverters' response to abnormal conditions in voltage and frequency, interruption in grid service, and cumulative power quality. No issues were identified to be caused by the interconnection of multiple devices.

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.

The Sandia Inverter Performance Test Protocol defined two possible weighted-average efficiency values for use in comparing inverter performance, of which one definition was selected by the California Energy Commission for use in their Buydown incentive program leading to widespread use in the photovoltaic inverter market. This paper discusses the derivation of the efficiency weights originally proposed, and investigates the potential for defining new weights in light of increased array-to-inverter (DC-to-AC) system rating ratios in modern PV systems.

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.

The performance of photovoltaic systems must be monitored accurately to ensure profitable long-term operation. The most important signals to be measured—irradiance and temperature, as well as power, current and voltage on both DC and AC sides of the system—contain rapid fluctuations that are not observable by typical monitoring systems. Nevertheless these fluctuations can affect the accuracy of the data that are stored. This report closely examines the main signals in one operating PV system, which were recorded at 2000 samples per second. It analyzes the characteristics and causes of the rapid fluctuations that are found, such as line-frequency harmonics, perturbations from anti-islanding detection, MPPT searching action and others. The operation of PV monitoring systems is then simulated using a wide range of sampling intervals, archive intervals and filtering options to assess how these factors influence data accuracy. Finally several potential sources of error are discussed with real-world examples.

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