Publications

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This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

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Voltage on the North American bulk system is normally regulated by synchronous generators, which typically are provided with voltage schedules by transmission system operators. In the past, variable generation plants were considered very small relative to conventional generating units, and were characteristically either induction generator (wind) or line-commutated inverters (photovoltaic) that have no inherent voltage regulation capability. However, the growing level of penetration of non-traditional renewable generation - especially wind and solar - has led to the need for renewable generation to contribute more significantly to power system voltage control and reactive power capacity. Modern wind-turbine generators, and increasingly PV inverters as well, have considerable dynamic reactive power capability, which can be further enhanced with other reactive support equipment at the plant level to meet interconnection requirements. This report contains a set of recommendations to the North-America Electricity Reliability Corporation (NERC) as part of Task 1-3 (interconnection requirements) of the Integration of Variable Generation Task Force (IVGTF) work plan. The report discusses reactive capability of different generator technologies, reviews existing reactive power standards, and provides specific recommendations to improve existing interconnection standards.

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As increasing numbers of photovoltaic (PV) systems are connected to utility systems, distribution engineers are becoming increasingly concerned about the risk of formation of unintentional islands. Utilities desire to keep their systems secure, while not imposing unreasonable burdens on users wishing to connect PV. However, utility experience with these systems is still relatively sparse, so distribution engineers often are uncertain as to when additional protective measures, such as direct transfer trip, are needed to avoid unintentional island formation. In the absence of such certainty, utilities must err on the side of caution, which in some cases may lead to the unnecessary requirement of additional protection. The purpose of this document is to provide distribution engineers and decision makers with guidance on when additional measures or additional study may be prudent, and also on certain cases in which utilities may allow PV installations to proceed without additional study because the risk of an unintentional island is extremely low. The goal is to reduce the number of cases of unnecessary application of additional protection, while giving utilities a basis on which to request additional study in cases where it is warranted.

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Sandia National Laboratories (Sandia) and SunPower Corporation (SunPower) have completed design and deployment of an autonomous irradiance monitoring system based on wireless mesh communications and a battery operated data acquisition system. The Lanai High-Density Irradiance Sensor Network is comprised of 24 LI-COR{reg_sign} irradiance sensors (silicon pyranometers) polled by 19 RF Radios. The system was implemented with commercially available hardware and custom developed LabVIEW applications. The network of solar irradiance sensors was installed in January 2010 around the periphery and within the 1.2 MW ac La Ola PV plant on the island of Lanai, Hawaii. Data acquired at 1 second intervals is transmitted over wireless links to be time-stamped and recorded on SunPower data servers at the site for later analysis. The intent is to study power and solar resource data sets to correlate the movement of cloud shadows across the PV array and its effect on power output of the PV plant. The irradiance data sets recorded will be used to study the shape, size and velocity of cloud shadows. This data, along with time-correlated PV array output data, will support the development and validation of a PV performance model that can predict the short-term output characteristics (ramp rates) of PV systems of different sizes and designs. This analysis could also be used by the La Ola system operator to predict power ramp events and support the function of the future battery system. This experience could be used to validate short-term output forecasting methodologies.

Sandia National Laboratories has developed a modeling approach to simulate time-synchronized, 1-minute power output from large PV plants in locations where only hourly irradiance measurements are available via satellite sources. The approach uses 1-min irradiance measurements from analogue sites in a similar geographic area. PV output datasets 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 singleaxis- tracked polycrystalline Si systems ranging in size from 5 to 300 MWAC. Simulated power output profiles at 1-min intervals were generated for five scenarios (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants. Copyright© (2011) by the American Solar Energy Society.

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This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

The 1.2-MW La Ola photovoltaic (PV) power plant in Lanai, Hawaii, has been in operation since December 2009. The host system is a small island microgrid with peak load of 5 MW. Simulations conducted as part of the interconnection study concluded that unmitigated PV output ramps had the potential to negatively affect system frequency. Based on that study, the PV system was initially allowed to operate with output power limited to 50% of nameplate to reduce the potential for frequency instability due to PV variability. Based on the analysis of historical voltage, frequency, and power output data at 50% output level, the PV system has not significantly affected grid performance. However, it should be noted that the impact of PV variability on active and reactive power output of the nearby diesel generators was not evaluated. In summer 2011, an energy storage system was installed to counteract high ramp rates and allow the PV system to operate at rated output. The energy storage system was not fully operational at the time this report was written; therefore, analysis results do not address system performance with the battery system in place.

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