Implementing state estimation in low and mediumvoltage power distribution is still challenging given the scale of many networks and the reliance of traditional methods on a large number of measurements. This paper proposes a method to improve voltage predictions in real-time by leveraging a limited set of real-time measurements. The method relies on Bayesian estimation formulated as a linear least squares estimation problem, which resembles the classical weighted least-squares (WLS) approach for scenarios where full network observability is not available. We build on recently developed linear approximations for unbalanced three-phase power flow to construct voltage predictions as a linear mapping of load predictions constructed with Gaussian processes. The estimation step to update the voltage forecasts in real-time is a linear computation allowing fast high-resolution state estimate updates. The uncertainty in forecasts can be determined a priori and smoothed a posteriori, making the method useful for both planning, operation and post-hoc analysis. The method outperforms conventional WLS and is applied to different test feeders and validated on a real test feeder with the utility Alliander in The Netherlands.

1 aDobbe, Roel1 avan Westering, Werner1 aLiu, Stephan1 aArnold, Daniel, B.1 aCallaway, Duncan, S.1 aTomlin, Claire uhttps://gridintegration.lbl.gov/publications/linear-single-and-three-phase-voltage01687nas a2200181 4500008004100000022001400041245008400055210006900139260001200208300001400220490000700234520109300241100002401334700001601358700002501374700002301399856008301422 2020 eng d a1949-305300aModel-Free Optimal Voltage Phasor Regulation in Unbalanced Distribution Systems0 aModelFree Optimal Voltage Phasor Regulation in Unbalanced Distri c01/2020 a884 - 8940 v113 aThe proliferation of voltage Phasor Measurement Units (PMUs) into electric power distribution grids presents new opportunities for utility operators to manage their systems more effectively. In particular, distribution-level PMUs can serve as proxy measurements for active and reactive power flows, thus alleviating the need for current transformer-based measurements for certain applications. In this work, we explore the use of distribution PMU measurements to optimally control line power flows without explicit measurements of these quantities and without a priori knowledge of the underlying distribution system topology. To do so, we extend a 2 dimensional Extremum Seeking (2D-ES) control paradigm to simultaneously manage Distributed Energy Resource (DER) active and reactive power contributions in unbalanced distribution systems. Simulation results show the ability of the proposed approach to virtually island different portions of a 3-phase unbalanced the network using DER injections while maintaining proper voltage magnitudes in the rest of the network.

1 aSankur, Michael, D.1 aDobbe, Roel1 avon Meier, Alexandra1 aArnold, Daniel, B. uhttps://gridintegration.lbl.gov/publications/model-free-optimal-voltage-phasor01998nas a2200205 4500008004100000022001400041245009600055210006900151260001200220300001600232490000700248520132000255100001601575700002401591700002601615700002301641700002501664700001901689856008401708 2020 eng d a1949-305300aToward Distributed Energy Services: Decentralizing Optimal Power Flow With Machine Learning0 aToward Distributed Energy Services Decentralizing Optimal Power c03/2020 a1296 - 13060 v113 aThe implementation of optimal power flow (OPF) methods to perform voltage and power flow regulation in electric networks is generally believed to require extensive communication. We consider distribution systems with multiple controllable Distributed Energy Resources (DERs) and present a data-driven approach to learn control policies for each DER to reconstruct and mimic the solution to a centralized OPF problem from solely locally available information. Collectively, all local controllers closely match the centralized OPF solution, providing near-optimal performance and satisfaction of system constraints. A rate distortion framework enables the analysis of how well the resulting fully decentralized control policies are able to reconstruct the OPF solution. The methodology provides a natural extension to decide what nodes a DER should communicate with to improve the reconstruction of its individual policy. The method is applied on both single- and three-phase test feeder networks using data from real loads and distributed generators, focusing on DERs that do not exhibit intertemporal dependencies. It provides a framework for Distribution System Operators to efficiently plan and operate the contributions of DERs to achieve Distributed Energy Services in distribution networks.

1 aDobbe, Roel1 aSondermeijer, Oscar1 aFridovich-Keil, David1 aArnold, Daniel, B.1 aCallaway, Duncan, S.1 aTomlin, Claire uhttps://gridintegration.lbl.gov/publications/toward-distributed-energy-services