Distributed Energy Resources (DER) have great potential to enhance the operation of electric power distribution systems. Previously, we explored the use of 2 Dimensional Extremum Seeking (2D-ES) control algorithms to enable model-free optimal control of DER to provide grid services to both the distribution and transmissions systems. Motivated by preliminary deployments of DER managed by 2D-ES algorithms in hardware-in-the-loop tests and in operational distribution grids, in this work, we extend the control scheme to accommodate communication delays and information loss.We propose a modification to the 2D-ES scheme to allow for the processing of batches of possibly noncontiguous objective function measurements at unknown and possibly uneven intervals. We provide a proof of the convergence of the batch 2D-ES (2D-BES) scheme when optimizing a generic convex objective function, as well as simulation results that demonstrate the suitability of the approach for substation active and reactive power target tracking.

1 aSankur, Michael, D.1 aBaudette, Maxime1 aMacDonald, Jason, S.1 aArnold, Daniel, B.1 aBui, Tung uhttps://gridintegration.lbl.gov/publications/batch-measurement-extremum-seeking01725nas a2200241 4500008004100000022001400041245009800055210006900153260001200222300001400234490000700248520096000255100002001215700002001235700001701255700002001272700001801292700002201310700002101332700002001353700002301373856008701396 2020 eng d a1949-305300aLearning Behavior of Distribution System Discrete Control Devices for Cyber-Physical Security0 aLearning Behavior of Distribution System Discrete Control Device c01/2020 a749 - 7610 v113 aConventional cyber-security intrusion detection systems monitor network traffic for malicious activity and indications that an adversary has gained access to the system. The approach discussed here expands the idea of a traditional intrusion detection system within electrical power systems, specifically power distribution networks, by monitoring the physical behavior of the grid. This is achieved through the use of high-rate distribution Phasor Measurement Units (PMUs), alongside SCADA packets analysis, for the purpose of monitoring the behavior of discrete control devices. In this work we present a set of algorithms for passively learning the control logic of voltage regulators and switched capacitor banks. Upon detection of an abnormal operation, the operator is alerted and further action can be taken. The proposed learning algorithms are validated on both simulated data and on measured PMU data from a utility pilot deployment site.

1 aRoberts, Ciaran1 aScaglione, Anna1 aJamei, Mahdi1 aGentz, Reinhard1 aPeisert, Sean1 aStewart, Emma, M.1 aMcParland, Chuck1 aMcEachern, Alex1 aArnold, Daniel, B. uhttps://gridintegration.lbl.gov/publications/learning-behavior-distribution-system01938nas a2200205 4500008004100000022001400041245010600055210006900161260001200230300001600242490000700258520125400265100001601519700002601535700001701561700002301578700002501601700001901626856008701645 2020 eng d a0885-895000aLinear Single- and Three-Phase Voltage Forecasting and Bayesian State Estimation With Limited Sensing0 aLinear Single and ThreePhase Voltage Forecasting and Bayesian St c11/2019 a1674 - 16830 v353 aImplementing 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-voltage01499nas a2200193 4500008004100000022001400041245007200055210006900127260001200196300001600208490000700224520088100231100002101112700001801133700002001151700002401171700002301195856008701218 2020 eng d a0885-895000aLossy DistFlow Formulation for Single and Multiphase Radial Feeders0 aLossy DistFlow Formulation for Single and Multiphase Radial Feed c11/2019 a1758 - 17680 v353 aA line loss approximation via parametrization is developed to improve performance of the simplified Baran and Wu DistFlow method, while maintaining a linear set of equations. The approach is evaluated on thousands of training feeders that are created to determine a numerically optimal setting for the parameterization. Feeders are generated using recent advances in synthetic network test case generation. The problem is formulated with the same structure as the simplified DistFlow, yet is more accurate given that line losses are explicitly expressed and quantified. The single-phase methodology is extended to multiphase systems by formulating matrix-vector equations that maintain an analogy to their single-phase counterpart. Results with approximated line losses are shown to also improve the accuracy of multiphase distribution system calculations.

1 aSchweitzer, Eran1 aSaha, Shammya1 aScaglione, Anna1 aJohnson, Nathan, G.1 aArnold, Daniel, B. uhttps://gridintegration.lbl.gov/publications/lossy-distflow-formulation-single-and01687nas 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-services01761nas a2200217 4500008004100000022001400041245009900055210006900154260001200223300001600235490000600251520104200257100001701299700001801316700002701334700003101361700001801392700002301410700002301433856008701456 2018 eng d a2156-338100aDistribution Voltage Regulation Using Extremum Seeking Control With Power Hardware-in-the-Loop0 aDistribution Voltage Regulation Using Extremum Seeking Control W c10/2018 a1824 - 18320 v83 aInteroperable distributed energy resources (DER), including photovoltaic (PV) inverters, are capable of providing a number of grid services by receiving commands from grid operators, aggregators, or other third parties. In many control scenarios, the grid operator must determine the operating mode and parameters for the devices to achieve a specific control objective. In this paper, we experimentally validate a distributed technique to achieve optimal DER reactive power operating points for distribution circuit voltage regulation using extremum seeking control. The method is demonstrated with physical and virtual DER connected to multiple hardware-in-the-loop distribution circuit simulations. This paper demonstrates PV inverters with realistic communication interfaces can receive real-time control signals from an aggregator and adjusting their reactive power to minimize voltage deviations. Simulations were conducted with fixed and variable solar irradiance to demonstrate the robustness of the approach.

1 aJohnson, Jay1 aSummers, Adam1 aDarbali-Zamora, Rachid1 aHernandez-Alvidrez, Javier1 aQuiroz, Jimmy1 aArnold, Daniel, B.1 aAnandan, Jithendar uhttps://gridintegration.lbl.gov/publications/distribution-voltage-regulation-using01790nas a2200181 4500008004100000022001400041245011300055210006900168260001200237300001400249490000700263520115600270100002301426700002401449700002901473700002501502856008101527 2017 eng d a0885-895000aModel-Free Optimal Coordination of Distributed Energy Resources for Provisioning Transmission-Level Services0 aModelFree Optimal Coordination of Distributed Energy Resources f c05/2017 a817 - 8280 v333 aCollective control of distributed energy resources (DER)-such as photovoltaic (PV) inverters or battery storage-have the potential to provide regulation services to the bulk electric grid. While optimal power flow techniques may be used to coordinate DER for this purpose, these approaches typically rely on accurate network models and a large number of system measurements. In this paper, we consider an approach that alleviates these modeling and measurement requirements. Here, we consider a two-dimensional adaptive control scheme known as extremum seeking, or ES, to perform optimization without knowledge of a model of the distribution network. We apply this scheme to enable simultaneous feeder head active power and voltage magnitude reference tracking, as well as feeder voltage regulation. From the perspective of the transmission grid, this approach essentially transforms the distribution feeder into a controllable (P,V) bus. Simulation results confirm the ability of the approach to track substation real power and voltage reference signals while maintaining distribution system voltages within acceptable tolerances.

1 aArnold, Daniel, B.1 aSankur, Michael, D.1 aNegrete-Pincetic, Matias1 aCallaway, Duncan, S. uhttps://gridintegration.lbl.gov/publications/model-free-optimal-coordination01845nas a2200157 4500008003900000245010400039210006900143260002400212520125500236100002201491700002001513700002301533700002501556700002001581856008601601 2015 d00aAccuracy and Validation of Measured and Modeled Data for Distributed PV Interconnection and Control0 aAccuracy and Validation of Measured and Modeled Data for Distrib aDenver, COc07/20153 aThe distribution grid is changing to become an active resource with complex modeling needs. The new active distribution grid will, within the next ten years, contain a complex mix of load, generation, storage and automated resources all operating with different objectives on different time scales from each other and requiring detailed analysis. Electrical analysis tools that are used to perform capacity and stability studies have been used for transmission system planning for many years. In these tools, the distribution grid was considered a load and its details and physical components were not modeled. The increase in measured data sources can be utilized for better modeling, but also control of distributed energy resources (DER). The utilization of these sources and advanced modeling tools will require data management, and knowledgeable users. Each of these measurement and modeling devices have accuracy constraints, which will ultimately define their future ability to be planned and controlled. This paper discusses the importance of measured data accuracy for inverter control, interconnection and planning tools and proposes ranges of control accuracy needed to satisfy all concerns based on the present grid infrastructure.

1 aStewart, Emma, M.1 aKiliccote, Sila1 aArnold, Daniel, B.1 avon Meier, Alexandra1 aArghandeh, Reza uhttps://gridintegration.lbl.gov/publications/accuracy-and-validation-measured-and01558nas a2200157 4500008003900000245006900039210006900108260001200177520100700189100002301196700002901219700002201248700002501270700002501295856008001320 2015 d00aExtremum Seeking Control of Smart Inverters for VAR Compensation0 aExtremum Seeking Control of Smart Inverters for VAR Compensation c09/20153 aReactive power compensation is used by utilities to ensure customer voltages are within pre-deﬁned tolerances and reduce system resistive losses. While much attention has been paid to model-based control algorithms for reactive power support and Volt Var Optimization (VVO), these strategies typically require relatively large communications capabilities and accurate models. In this work, a non-model-based control strategy for smart inverters is considered for VAR compensation. An Extremum Seeking control algorithm is applied to modulate the reactive power output of inverters based on real power information from the feeder substation, without an explicit feeder model. Simulation results using utility demand information conﬁrm the ability of the control algorithm to inject VARs to minimize feeder head real power consumption. In addition, we show that the algorithm is capable of improving feeder voltage proﬁles and reducing reactive power supplied by the distribution substation.

1 aArnold, Daniel, B.1 aNegrete-Pincetic, Matias1 aStewart, Emma, M.1 aAuslander, David, M.1 aCallaway, Duncan, S. uhttps://gridintegration.lbl.gov/publications/extremum-seeking-control-smart