Publications

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This paper discusses the broad use of rotational kinetic energy stored in wind turbine rotors to supply services to the electrical power grid. The grid services are discussed in terms of zero-net-energy, which do not require a reduction in power output via pitch control (spill), but neither do they preclude doing so. The services discussed include zero-net-energy regulation, transient and small signal stability, and other frequency management services. The delivery of this energy requires a trade-off between the frequency and amplitude of power modulation and is limited, in some cases, by equipment ratings and the unresearched long-term mechanical effects on the turbine. As wind displaces synchronous generation, the grid's inertial storage is being reduced, but the amount of accessible kinetic energy in a wind turbine at rated speed is approximately 6 times greater than that of a generator with only a 0.12% loss in efficiency and 75 times greater at 10% loss. The potential flexibility of the wind's kinetic storage is also high. However, the true cost of providing grid services using wind turbines, which includes a potential increase in operations and maintenance costs, have not been compared to the value of the services themselves.

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The PV lifetime project must select a sample size (number of PV modules) for each PV system to be deployed. In this memorandum, we show how the uncertainty in measured degradation depends on the selected sample size.

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Short circuit current (Isc) depends on the effective irradiance incident upon a PV module. Effective irradiance is highly correlated with broadband irradiance, but can vary slightly as the spectral content of the incident light changes. We explore using a few spectral wavelengths with broadband irradiance to predict Isc for ten modules of varying technologies (silicon, CIGS, CdTe). The goal is to identify a few spectral wavelengths that could be easily (and economically) measured to improve PV performance modeling.

PVLIB is a set of open source modeling functions that allow users to simulate most aspects of PV system performance. The functions, in Matlab and Python, are freely available under a BSD 3 clause open source license. The Matlab version is maintained by Sandia and is available on the PV Performance Modeling Collaborative (PVPMC) website (pvpmc.sandia.gov). The Python version is available on GitHub with packages easily installable through conda and pip. New functions were released on the Matlab version 1.3 in January 2016 and are actively being ported to Python.

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.

The Sandia Array Performance Model (SAPM), a semi-empirical model for predicting PV system power, has been in use for more than a decade. While several studies have presented laboratory intercomparisons of measurements and analysis, detailed procedures for determining model coefficients have never been published. Independent test laboratories must develop in-house procedures to determine SAPM coefficients, which contributes to uncertainty in the resulting models. In response to requests from commercial laboratories and module manufacturers, Sandia has formally documented the measurement and analysis methods as a supplement to the original model description. In this paper we present a description of the measurement procedures and an example analysis for calibrating the SAPM.

PVLIB is a set of open source modeling functions that allow users to simulate most aspects of PV system performance. The functions, in Matlab and Python, are freely available under a BSD 3 clause open source license. The Matlab version is maintained by Sandia and is available on the PV Performance Modeling Collaborative (PVPMC) website (pvpmc.sandia.gov). The Python version is available on GitHub with packages easily installable through conda and pip. New functions were released on the Matlab version 1.3 in January 2016 and are actively being ported to Python.

Determination of module temperature coefficients for voltage, current and power requires measuring the average of cell temperatures. Conventional practice is to place thermocouples or resistive temperature devices (RTDs) at a few locations on a module's back surface and to average the readings, which may not accurately represent the average temperature over all cells. We investigate the suitability of averaging RTDs, which measure average temperature along a 1m length, to accurately measure the average cell temperature when determining temperature coefficients outdoors.