Publications

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This report investigates the effects that increased distributed photovoltaic (PV) generation would have on the Kauai Island Utility Co-op (KIUC) system operating requirements. The study focused on determining reserve requirements needed to mitigate the impact of PV variability on system frequency, and the impact on operating costs. Scenarios of 5-MW, 10-MW, and 15-MW nameplate capacity of PV generation plants distributed across the Kauai Island were considered in this study. The analysis required synthesis of the PV solar resource data and modeling of the KIUC system inertia. Based on the results, some findings and conclusions could be drawn, including that the selection of units identified as marginal resources that are used for load following will change; PV penetration will displace energy generated by existing conventional units, thus reducing overall fuel consumption; PV penetration at any deployment level is not likely to reduce system peak load; and increasing PV penetration has little effect on load-following reserves. The study was performed by EnerNex under contract from Sandia National Laboratories with cooperation from KIUC.

We present an approach to simulate time-synchronized, one-minute power output from large photovoltaic (PV) generation plants in locations where only hourly irradiance estimates are available from satellite sources. The approach uses one-minute irradiance measurements from ground sensors in a climatically and geographically similar area. Irradiance is translated to power using the Sandia Array Performance Model. Power output is generated for 2007 in southern Nevada are being used for a Solar PV Grid Integration Study to estimate the integration costs associated with various utility-scale PV generation levels. Plant designs considered include both fixed-tilt thin-film, and single-axis-tracked polycrystalline Si systems ranging in size from 5 to 300 MW{sub AC}. Simulated power output profiles at one-minute intervals were generated for five scenarios defined by total PV capacity (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants.

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High frequency irradiance variability measured on the ground is caused by the formation, dissipation, and passage of clouds in the sky. If we can identify and associate different cloud types/patterns from satellite imagery, we may be able to predict irradiance variability in areas lacking sensors. With satellite imagery covering the entire U.S., this allows for more accurate integration planning and power flow modeling over wide areas. Satellite imagery from southern Nevada was analyzed at 15 minute intervals over a year. Methods for image stabilization, cloud detection, and textural classification of clouds were developed and tested. High Performance Computing parallel processing algorithms were also investigated and tested. Artificial Neural Networks using imagery as inputs were trained on ground-based measurements of irradiance to model the variability and were tested to show some promise as a means for predicting irradiance variability.

We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.

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Expanded testing capabilities at Sandia National Laboratories Distributed Energy Technologies Lab (DETL) now include a single phase μGrid research test bed platform. This reconfigurable μGrid topology test bed platform is being utilized to evaluate control strategies and communication algorithms and associated issues applicable to high penetration of distributed resources on the grid. To demonstrate coordinated μGrid functionality, battery based Xantrex inverters were integrated in a μGrid configuration along with custom centralized LabVIEW generated virtual Energy Management System (EMS) software to provide system wide control. Enhanced μGrid cooperation was implemented by invoking control schemes based on existing Xantrex inverter command sets issued over a standard communication interface. Inverter cooperation was achieved without additional modifications to embedded software. This paper outlines test configuration and results for cooperative storage management and voltage support scenarios. ©2009 IEEE.

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