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Emma M. Stewart

Publications and source records attributed to Emma M. Stewart.

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Optimal Voltage Phasor Regulation for Switching Actions in Unbalanced Distribution Systems

The proliferation of phasor measurement units (PMUs) into electric power distribution grids presents new opportunities for utility operators to manage distribution systems more effectively. One potential application of PMU measurements is to facilitate distribution grid re-configuration. Given the increasing amount of Distributed Energy Resource (DER) penetration into distribution grids, in this work we formulate an Optimal Power Flow (OPF) approach that manages DER power injections to minimize the voltage phasor difference between two nodes on a distribution network to enable efficient network reconfiguration. In order to accomplish this, we develop a linear model that relates voltage phase angles to real and reactive power flows in unbalanced distribution systems. Used in conjunction with existing linearizations relating voltage magnitude differences to power flows, we formulate an OPF capable of minimizing voltage phasor differences across different points in the network. In simulations, we explore the use of the developed approach to minimize the phasor difference across switches to be opened or closed, thereby providing an opportunity to automate and increase the speed of reconfigurations in unbalanced distribution grids.

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Towards Real-Time Estimation of Solar Generation From Micro-Synchrophasor Measurements

This paper presents a set of methods for estimating the renewable energy generation downstream of a measurement device using real-world measurements. First, we present a generation disaggregation scheme where the only information available for estimation is the micro-synchrophasor measurements obtained at the substation or feeder head. We then propose two strategies in which we use measurements from the substation as well as a proxy solar irradiance measurement. Using these two measurement points, we first propose a multiple linear regression strategy, in which we estimate a relationship between the measured reactive power and the load active power consumption, which are then used in disaggregation. Finally, we expand this strategy to strategically manage the reconstruction errors in the estimators. We simultaneously disaggregate the solar generation and load. We show that it is possible to disaggragate the generation of a 7.5 megawatt photovoltaic site with a root-mean-squared error of approximately 450 kilowatts.

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