Publications

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The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation and regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.

Accurately representing the local solar variability at timescales relevant to distribution grid operations (30-s and shorter) is essential to modeling the impact of solar photovoltaics (PV) on distribution feeders. Due to a lack of available high-frequency solar data, some distribution grid studies have used synthetically-created PV variability or measured PV variability from a different location than their study location. In this work, we show the importance of using accurate solar PV variability inputs in distribution studies. Using high-frequency solar irradiance data from 10 locations in the United States, we compare the ramp rate distributions at the different locations, use a quantitative metric to describe the solar variability at each location, and run distribution simulations using representative 1-week samples from each location to demonstrate the impact of locational solar variability on the number of voltage regulator tap change operations. Results show more than a factor of 3 difference in the number of tap change operations between different PV power variability samples based on irradiance from the different locations. Errors in simulated number of tap changes of up to -70% were found when using low-frequency (e.g., 15-min) solar variability.

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 functio ns 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 th e 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 i n 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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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.

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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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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