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Evaluation of reactive power control capabilities of residential PV in an unbalanced distribution feeder

2014 IEEE 40th Photovoltaic Specialist Conference, PVSC 2014

Seuss, John; Reno, Matthew J.; Broderick, Robert J.; Harley, Ronald G.

The use of residential PV grid-tie inverters to supply reactive power as a benefit to the distribution grid has been widely proposed, however, there is little insight into how much of a benefit can be achieved from this control under varying system operating points. This paper seeks to demonstrate the effectiveness of a linearized versus nonlinear reactive power dispatch solution on a highly unbalanced distribution feeder under differing load profiles, insolation levels, and penetration rates of PV in the feeder. The results are analyzed to determine the system operating points that are favorable to reactive power control and the overall effectiveness of each solution in realistic feeder states.

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Locational dependence of PV hosting capacity correlated with feeder load

Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference

Coogan, Kyle; Reno, Matthew J.; Grijalva, Santiago; Broderick, Robert J.

With rising adoption of solar energy, it is increasingly important for utilities to easily assess potential interconnections of photovoltaic (PV) systems. In this analysis, we show the maximum feeder voltage due to various PV interconnections and provide visualizations of the PV impact to the distribution system. We investigate the locational dependence of PV hosting capacity by examining the impact of PV system size on these voltages with regard to PV distance and resistance to the substation. We look at the effect of increasing system size on line loading and feeder violations. The magnitude of feeder load is also considered as an independent variable with repeated analyses to determine the effect on the PV impact analysis. A technique is presented to determine and visualize the maximum capacity for possible PV installations for distribution feeders.

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Grid integrated distributed PV (GridPV)

Reno, Matthew J.

This manual provides the documentation of the MATLAB toolbox of functions for using OpenDSS to simulate the impact of solar energy on the distribution system. The majority of the functions are useful for interfacing OpenDSS and MATLAB, and they are of generic use for commanding OpenDSS from MATLAB and retrieving information from simulations. A set of functions is also included for modeling PV plant output and setting up the PV plant in the OpenDSS simulation. The toolbox contains functions for modeling the OpenDSS distribution feeder on satellite images with GPS coordinates. Finally, example simulations functions are included to show potential uses of the toolbox functions. Each function in the toolbox is documented with the function use syntax, full description, function input list, function output list, example use, and example output.

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Time series power flow analysis for distribution connected PV generation

Ellis, Abraham E.; Quiroz, Jimmy E.; Reno, Matthew J.; Broderick, Robert J.

Distributed photovoltaic (PV) projects must go through an interconnection study process before connecting to the distribution grid. These studies are intended to identify the likely impacts and mitigation alternatives. In the majority of the cases, system impacts can be ruled out or mitigation can be identified without an involved study, through a screening process or a simple supplemental review study. For some proposed projects, expensive and time-consuming interconnection studies are required. The challenges to performing the studies are twofold. First, every study scenario is potentially unique, as the studies are often highly specific to the amount of PV generation capacity that varies greatly from feeder to feeder and is often unevenly distributed along the same feeder. This can cause location-specific impacts and mitigations. The second challenge is the inherent variability in PV power output which can interact with feeder operation in complex ways, by affecting the operation of voltage regulation and protection devices. The typical simulation tools and methods in use today for distribution system planning are often not adequate to accurately assess these potential impacts. This report demonstrates how quasi-static time series (QSTS) simulation and high time-resolution data can be used to assess the potential impacts in a more comprehensive manner. The QSTS simulations are applied to a set of sample feeders with high PV deployment to illustrate the usefulness of the approach. The report describes methods that can help determine how PV affects distribution system operations. The simulation results are focused on enhancing the understanding of the underlying technical issues. The examples also highlight the steps needed to perform QSTS simulation and describe the data needed to drive the simulations. The goal of this report is to make the methodology of time series power flow analysis readily accessible to utilities and others responsible for evaluating potential PV impacts.

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Using cloud classification to model solar variability

42nd ASES National Solar Conference 2013, SOLAR 2013, Including 42nd ASES Annual Conference and 38th National Passive Solar Conference

Reno, Matthew J.; Stein, Joshua S.

Imagery from GOES satellites is analyzed to determine how solar variability is related to the NOAA classification of cloud type. Without using a model to convert satellite imagery to average insolation on the ground, this paper investigates using cloud categories to directly model the expected statistical variability of ground irradiance. Hourly cloud classified satellite images are compared to multiple years of ground measured irradiance at two locations to determine if measured irradiance, ramp rates, and variability index are correlated with cloud category. Novel results are presented for ramp rates grouped by the cloud category during the time period. This correlation between satellite cloud classification and solar variability could be used to model the solar variability for a given location and time and could be used to determine the variability of a location based on the prevalence of each cloud category.

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The variability index: A new and novel metric for quantifying irradiance and pv output variability

World Renewable Energy Forum, WREF 2012, Including World Renewable Energy Congress XII and Colorado Renewable Energy Society (CRES) Annual Conferen

Stein, Joshua S.; Hansen, Clifford H.; Reno, Matthew J.

Variability of photovoltaic (PV) power output is a potential concern to utilities because it can lead to voltage changes on the distribution system and have other adverse impacts on power quality unless additional equipment is added or operational practices are changed to mitigate these effects. This paper develops and evaluates a simple yet novel approach for quantifying irradiance variability over various timescales. The approach involves comparison between measured irradiance and a reference, clear sky irradiance, determined from a model. Conceptually, the "Variability Index" is the ratio of the "length" of the measured irradiance plotted against time divided by the "length" of the reference clear sky irradiance signal. Adjustments are proposed that correct for different measurement intervals. By evaluating the variability index at several sites, we show how annual and monthly distributions of this metric can help to classify sites and periods of time when variability is significant. Copyright © (2012) by American Solar Energy Society.

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PV output variability modeling using satellite imagery and neural networks

Conference Record of the IEEE Photovoltaic Specialists Conference

Reno, Matthew J.; Stein, Joshua S.

High frequency irradiance variability measured on the ground is caused by the formation, dissipation, and passage of clouds in the sky. Variability and ramp rates of PV systems are increasingly important to understand and model for grid stability as PV penetration levels rise. Using satellite imagery to identify cloud types and patterns can 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 modelling 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. Artificial Neural Networks, cloud texture analysis, and cloud type categorization can be used to model the irradiance and variability for a location at a one minute resolution without needing many ground based irradiance sensors. © 2012 IEEE.

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Results 301–325 of 330
Results 301–325 of 330