Publications

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We describe an open source evaluation framework for solar forecasting to support the DOE Solar Forecasting 2 program and the broader solar forecast community. The framework enables evaluations of solar irradiance, solar power, and net-load forecasts that are impartial, repeatable and auditable. First, we define the use cases of the framework. The use cases, developed from the project's initial stakeholder engagement sessions, include comparisons to reference data sets, private forecast trials, evaluation of probabilistic forecast skill, and examinations of forecast errors during critical periods. We discuss the framework's data validation toolkit, reference data sources, and data privacy protocols. We describe the framework's benchmark forecast capabilities for intra-hour and day ahead forecast horizons. Finally, we summarize the reports and metrics that communicate the relative merits of the test and benchmark forecasts. The reports are created from standardized templates and include graphics for quantitatively evaluating deterministic and probabilistic forecasts and standard metrics for quantitatively evaluating forecasts.

In this paper, we present a new, light-weight approach for extracting the five single diode parameters (IL, Io, RS, RSH, and nNsVt) for advanced, in-field monitoring of in situ current and voltage (I-V) tracing devices. The proposed procedure uses individual I-V curves, and does not require the irradiance or module temperature measurement to calculate the parameters. It is suitable for operation on a small, single board computer at the point of I-V curve measurement. This allows for analysis to occur in the field, and eliminates the need to transfer large amounts of data to centralized databases. Observers can receive alerts directly from the in-field devices based on the extraction, and analysis of the commonly used single diode equivalent model parameters. This paper defines the approach and evaluates its accuracy by subjecting it to I-V curves with known parameters. Its performance is defined using actual I-V curves generated from an in situ scanning devices installed within an actual photovoltaic production field. The algorithm is able to operate at a high accuracy for multiple module types and performed well on actual curves extracted in the field.

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Literature describes various methods for determining a series resistance for a photovoltaic device from measured IV curves. We investigate use of these techniques to estimate the series resistance parameter for a single diode equivalent circuit model. With simulated IV curves we demonstrate that the series resistance values obtained by these techniques differ systematically from the known series resistance parameter values used to generate the curves, indicating that these methods are not suitable for determining the series resistance parameter for the single diode model equation. We present an alternative method to determine the series resistance parameter jointly with the other parameters for the single diode model equation, and demonstrate the accuracy and reliability of this technique in the presence of measurement errors.

While the concept of aggregating and controlling renewable distributed energy resources (DERs) to provide grid services is not new, increasing policy support of DER market participation has driven research and development in algorithms to pool DERs for economically viable market participation. Sandia National Laboratories recently undertook a three-year research program to create the components of a real-world virtual power plant (VPP) that can simultaneously participate in multiple markets. Our research extends current state-of-the-art rolling horizon control through the application of stochastic programming with risk aversion at various time resolutions. Our rolling horizon control consists of (1) day-ahead optimization to produce an hourly aggregate schedule for the VPP operator and (2) sub-hourly optimization for real-time dispatch of each VPP subresource. Both optimization routines leverage a two-stage stochastic program (SP) with risk aversion, and integrate the most up-to-date forecasts to generate probabilistic scenarios in real operating time. Our results demonstrate the benefits to the VPP operator of constructing a stochastic solution regardless of the weather. In more extreme weather, applying risk optimization strategies can dramatically increase the financial viability of the VPP. As a result, the methodologies presented here can be further tailored for optimal control of any VPP asset fleet and its operational requirements.

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In this paper, we present the effect of installation parameters (tilt angle, height above ground, and albedo) on the bifacial gain and energy yield of three south-facing photovoltaic (PV) system configurations: a single module, a row of five modules, and five rows of five modules utilizing RADIANCE-based ray tracing model. We show that height and albedo have a direct impact on the performance of bifacial systems. However, the impact of the tilt angle is more complicated. Seasonal optimum tilt angles are dependent on parameters such as height, albedo, size of the system, weather conditions, and time of the year. For a single bifacial module installed in Albuquerque, NM, USA (35 °N) with a reasonable clearance (∼1 m) from the ground, the seasonal optimum tilt angle is lowest (∼5°) for the summer solstice and highest (∼65°) for the winter solstice. For larger systems, seasonal optimum tilt angles are usually higher and can be up to 20° greater than that for a single module system. Annual simulations also indicate that for larger fixed-tilt systems installed on a highly reflective ground (such as snow or a white roofing material with an albedo of ∼81%), the optimum tilt angle is higher than the optimum angle of the smaller size systems. We also show that modules in larger scale systems generate lower energy due to horizon blocking and large shadowing area cast by the modules on the ground. For albedo of 21%, the center module in a large array generates up to 7% less energy than a single bifacial module. To validate our model, we utilize measured data from Sandia National Laboratories' fixed-tilt bifacial PV testbed and compare it with our simulations.

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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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