We discuss a framework for coordinating the response of distributed energy resources (DERs) connected to electric power distribution networks to provide frequency regulation services. These resources include plug-in electric vehicles, thermostatically controlled loads, and microturbines. In this framework, we consider an aggregator that participates in the real-time market by submitting an offer to provide frequency regulation services. If the offer is accepted, the aggregator needs to coordinate the response of a set of DERs. The DERs are compensated through bilateral contracts, the terms of which are negotiated in advance. The DER coordination problem the aggregator is faced with is cast as an optimal control problem, and we propose a bilayer framework to obtain a sub-optimal solution. In the first layer, we utilize model-predictive control techniques driven by regulation signal forecasts and parameter estimates to obtain a reference control signal for the DERs. A second control layer provides closed-loop regulation around the reference computed by the top layer, which minimizes the error that arises due to forecast error, plant-model mismatch, and the slower speed of the optimal control.

1 aHughes, Justin, T.1 aDominguez-Garcia, Alejandro, D.1 aPoolla, Kameshwar uhttp://aisel.aisnet.org/hicss-50/es/renewable_resources/3/01588nas a2200145 4500008003900000245013200039210006900171260003500240300001000275520101600285653001301301100002101314700003601335856007101371 2016 d00aAugmenting the power system toolbox: Enabling automatic generation control and providing a platform for cyber security analysis0 aAugmenting the power system toolbox Enabling automatic generatio aDenver, CO, USAbIEEEc09/2016 a1 - 53 aThe Power System Toolbox (PST) is a MATLAB-based package for simulating power system electromechanical dynamics. In this paper, we report on code that we developed to augment the capabilities of the PST, which enables the possibility of including the automatic generation control (AGC) system in simulations. In the process, we have also modified the linearization capability of the PST so as to include the effect of the AGC system when enabled in the simulation. The augmented PST package can be easily utilized for simulation studies in different applications. As an example, we focus on its utilization for assessing the impact of cyber events on power system dynamic performance. Specifically, by using the augmented PST package, users can inject various measurement errors and communication delays to signals that are used by the AGC system, and simulate the effect of such cyber events on system dynamic performance. We present several case studies to illustrate the new features added to the PST.

10aRM15-0011 aZhang, Jiangmeng1 aDominguez-Garcia, Alejandro, D. uhttps://certs.lbl.gov/publications/augmenting-power-system-toolbox01890nas a2200169 4500008003900000022001400039245006400053210006400117260001200181300001100193520134500204653001301549100002301562700003601585700002201621856007701643 2016 d a0885-895000aIdentification of Virtual Battery Models for Flexible Loads0 aIdentification of Virtual Battery Models for Flexible Loads c01/2016 a1 - 103 aThe increasing prevalence of technologies such as advanced metering and controls and continuously variable power electronic devices are enabling a radical shift in the way frequency regulation is performed in the bulk power system. This is a welcome development in light of the increase of unpredictable and variable generation. The idea of active participation of loads in frequency markets is not new, but the rapidly changing landscape of the power grid requires new techniques for successful integration of new types of resources; this paper works towards that end. Previously, it has been shown that residential HVAC systems can be aggregated and used to provide frequency regulation by utilizing their thermal energy capacity and flexibility of energy consumption. The virtual battery model—a first-order linear dynamical model—was analytically shown to be an accurate and simple model to capture the flexibility of residential HVAC systems. This paper presents a technique for creating the same battery-type models for many other types of systems, which can be much more complex. Our technique is based on stress testing detailed software models of physical systems. A realistic case study involving the terminal building of a small airport is presented as evidence of the effectiveness of the proposed techniques.

10aRM15-0011 aHughes, Justin, T.1 aDominguez-Garcia, Alejandro, D.1 aPoolla, Kameshwar uhttps://certs.lbl.gov/publications/identification-virtual-battery-models01337nas a2200157 4500008003900000022001400039245008500053210006900138260001200207300001000219520080900229653001301038100002101051700003601072856007101108 2016 d a1949-305300aOn the Impact of Measurement Errors on Power System Automatic Generation Control0 aImpact of Measurement Errors on Power System Automatic Generatio c08/2016 a1 - 13 aIn this paper, we propose a framework to evaluate the impact on power system dynamic performance of different types of errors in the measurements utilized by the automatic generation control (AGC) system. To address the random nature of these errors, stochastic system analysis methods are utilized to evaluate the statistics of system state variables. By examining the convergence properties of these statistics, errors that cause instability are identified. A reduced-order model, obtained by using singular perturbation arguments, is also formulated that enables us to provide analytical expressions capturing the impact of the errors. The proposed method is illustrated and verified through several case studies with different types of errors on a simplified New England/New York system model.

10aRM15-0011 aZhang, Jiangmeng1 aDominguez-Garcia, Alejandro, D. uhttps://certs.lbl.gov/publications/impact-measurement-errors-power01646nas a2200157 4500008003900000245005000039210004800089260003500137300001000172520113800182653001301320100002201333700003601355700002101391856007601412 2015 d00aMeasurement-based real-time economic dispatch0 aMeasurementbased realtime economic dispatch aDenver, CO, USAbIEEEc07/2015 a1 - 53 aIn this paper, we propose a measurement-based approach to the real-time economic dispatch (ED). The realtime ED is a widely used market scheduling problem seeking to economically balance electricity system supply and demand and provide locational marginal prices (LMPs) while respecting system reliability requirements. The ED is a convex optimization problem with a linear or quadratic objective, typically the minimization of generator costs or the maximization of social surplus. The constraints capture power balance and network flow capacity limits and are formulated using a linearized power flow model. Our approach utilizes power system sensitivities estimated from phasor measurement unit (PMU) measurements to reformulate the model-based power flow and network flow constraints. The resulting measurement-based real-time ED overcomes the vulnerabilities of the model-based real-time ED. The dispatch instructions and LMPs calculated with our measurement-based real-time ED accurately, and adaptively, reflect real-time system conditions. We illustrate the strengths of the proposed approach via several case studies.

10aAA05-0051 aVan Horn, Kai, E.1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/measurement-based-real-time-economic01739nas a2200181 4500008003900000022001400039245007100053210006800124260001200192300001100204490000700215520116700222653001301389100002201402700003601424700002101460856007601481 2015 d a0885-895000aMeasurement-Based Real-Time Security-Constrained Economic Dispatch0 aMeasurementBased RealTime SecurityConstrained Economic Dispatch c12/2015 a1 - 130 vPP3 aIn this paper, we propose a measurement-based approach to the real-time security-constrained economic dispatch (SCED). The real-time SCED is a widely used market scheduling tool that seeks to economically balance electricity supply and demand and provide locational marginal prices (LMPs), while ensuring system reliability standards are met. To capture network flows and security considerations, the conventional SCED formulation relies on sensitivities that are typically computed from a linearized power flow model, which is vulnerable to phenomena such as undetected topology changes, changes in the system operating point, and the existence of incorrect model data. Our approach to the formulation of the SCED problem utilizes power system sensitivities estimated from phasor measurement unit (PMU) measurements. The resulting measurement-based real-time SCED is robust against the aforementioned phenomena. Moreover, the dispatch instructions and LMPs calculated with the proposed measurement-based SCED accurately reflect real-time system conditions and security needs. We illustrate the strengths of the proposed approach via several case studies.

10aAA05-0051 aVan Horn, Kai, E.1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/measurement-based-real-time-security01622nas a2200157 4500008003900000245004800039210004700087260003800134300001000172520111500182653001301297100002201310700003601332700002101368856007501389 2015 d00aSensitivity-based line outage angle factors0 aSensitivitybased line outage angle factors aCharlotte, NC, USAbIEEEc10/2015 a1 - 53 aIn this paper, we propose a model-based approach to the computation of line outage angle factors (LOAFs), which relies on the use of angle factors (AFs) and power transfer distribution factors (PTDFs). A LOAF provides the sensitivity of the voltage angle difference between the terminal buses of a transmission line in the event the line is outaged to the pre-outage active power flow on the line. Large angle differences between the terminal buses of an outaged line can prevent the successful reclosure of the line-such an event was a significant contributing factor to the 2011 San Diego blackout. The proposed model-based LOAFs, along with the AFs and injection shift factors (ISFs), enable the fast computation of the impact on the angle across lines of line outages and active power injections, and provide system operators a systematic mean by which to assess line outage angles and undertake the appropriate dispatch actions necessary to alleviate large phase angle differences. We demonstrate the effectiveness of the proposed LOAFs with a case study carried out on the IEEE 14-bus test system.

10aAA05-0051 aVan Horn, Kai, E.1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/sensitivity-based-line-outage-angle01673nas a2200169 4500008003900000245007400039210006900113260002900182520101900211653001901230653002801249653001301277100001701290700003601307700002201343856013801365 2015 d00aVirtual Battery Models for Load Flexibility from Commercial Buildings0 aVirtual Battery Models for Load Flexibility from Commercial Buil aKauai, HIbIEEEc01/20153 aFrequency regulation is becoming increasingly important with deeper penetration of variable generation resources. Flexible loads have been proposed as a low-cost provider of frequency regulation. For example, the flexibility of loads with inherent thermal energy storage resides in their ability to vary their electricity consumption without compromising their end function. In this context, the aggregate flexibility of a collection of diverse residential air-conditioning loads has previously been shown to be well modeled as a virtual battery using first principles load models. This analytical method will not scale to more complex flexible loads such as commercial HVAC systems. This paper presents a method to identify virtual battery model parameters for these more complex flexible loads. The method extracts the parameters of the virtual battery model by stress-testing a detailed software model of the physical system. Synthetic examples reveal the effectiveness of the proposed identification technique.10aflexible loads10areliability and markets10aRM11-0061 aHughes, J.T.1 aDominguez-Garcia, Alejandro, D.1 aPoolla, Kameshwar uhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7070131&refinements%3D4254602198%26filter%3DAND%28p_IS_Number%3A7069647%2901444nas a2200169 4500008003900000245009500039210006900134260003600203300001000239520085000249653000901099653001001108100002401118700003601142700002101178856007501199 2014 d00aGeneralized injection shift factors and application to estimation of power flow transients0 aGeneralized injection shift factors and application to estimatio aPullman, WA, USAbIEEEc09/2014 a1 - 53 aThis paper proposes a method to estimate transmission line flows in a power system during the transient period following a loss of generation or increase in load contingency by using linear sensitivity injection shift factors (ISFs). Traditionally, ISFs are computed from an offline power flow model of the system with the slack bus defined. The proposed method, however, relies on generalized ISFs estimated via the solution of a system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. Even though the generalized ISFs are obtained at the pre-disturbance steady-state operating point, by leveraging inertial and governor power flows during appropriate time-scales, they can be manipulated to predict active transmission line flows during the post-contingency transient period.10aAARD10aCERTS1 aChen, Yu, Christine1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/generalized-injection-shift-factors01636nas a2200241 4500008003900000022001400039245009300053210006900146260001100215300001600226490000700242520084900249653000901098653003901107653001001146653001801156653003601174653002801210100002401238700003601262700002101298856007501319 2014 d a0885-895000aMeasurement-Based Estimation of Linear Sensitivity Distribution Factors and Applications0 aMeasurementBased Estimation of Linear Sensitivity Distribution F c5/2014 a1372 - 13820 v293 aIn this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real-time. The method does not rely on the system power flow model. Instead, it uses only high-frequency synchronized data collected from phasor measurement units to estimate the injection shift factors through linear least-squares estimation, after which other DFs can be easily computed. Such a measurement-based approach is desirable since it is adaptive to changes in system operating point and topology. We further improve the adaptability of the proposed approach to such changes by using weighted and recursive least-squares estimation. Through numerical examples, we illustrate the advantages of our proposed DF estimation approach over the conventional model-based one in the context of contingency analysis and generation re-dispatch.10aAARD10aAutomatic Switchable Network (ASN)10aCERTS10aload modeling10aphasor measurement units (PMUs)10apower system monitoring1 aChen, Yu, Christine1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/measurement-based-estimation-linear01689nas a2200169 4500008003900000022001400039245009500053210006900148260001200217300001100229520111200240653000901352100002401361700003601385700002101421856007701442 2014 d a0885-895000aA Sparse Representation Approach to Online Estimation of Power System Distribution Factors0 aSparse Representation Approach to Online Estimation of Power Sys c10/2014 a1 - 123 aIn this paper, we propose a method to compute linear sensitivity distribution factors (DFs) in near real time without relying on a power flow model of the system. Specifically, we compute the injection shift factors (ISFs) of a particular line of interest with respect to active power injections at all buses (all other DFs can be determined from ISFs). The proposed ISF estimation method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. We exploit a sparse representation (i.e., one in which many elements are zero) of the vector of desired ISFs via rearrangement by electrical distance and an appropriately chosen linear transformation, and cast the estimation problem into a sparse vector recovery problem. As we illustrate through case studies, the proposed approach provides accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors estimation method. 10aAARD1 aChen, Yu, Christine1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/sparse-representation-approach-online01617nas a2200217 4500008003900000245009600039210006900135260003800204300001000242520084800252653000901100653003901109653001001148653002501158653003601183653002901219100002401248700003601272700002101308856007001329 2013 d00aOnline estimation of power system distribution factors — A sparse representation approach0 aOnline estimation of power system distribution factors A sparse aManhattan, KS, USAbIEEEc09/2013 a1 - 53 aThis paper proposes a method to compute linear sensitivity distribution factors (DFs) in near real-time without relying on a power flow model of the system. Instead, the proposed method relies on the solution of an underdetermined system of linear equations that arise from high-frequency synchronized measurements obtained from phasor measurement units. In particular, we exploit a sparse representation (i.e., one in which many elements are zero) of the desired DFs obtained via a linear transformation, and cast the estimation problem as an IO-norm minimization. As we illustrate through examples, the proposed approach is able to provide accurate DF estimates with fewer sets of synchronized measurements than earlier approaches that rely on the solution of an overdetermined system of equations via the least-squares errors method.

10aAARD10aAutomatic Switchable Network (ASN)10aCERTS10adistribution factors10aphasor measurement units (PMUs)10apower system reliability1 aChen, Yu, Christine1 aDominguez-Garcia, Alejandro, D.1 aSauer, Peter, W. uhttps://certs.lbl.gov/publications/online-estimation-power-system01902nas a2200193 4500008003900000020002200039245007600061210006900137260003400206300001600240520125400256653000901510653002801519653001301547100002401560700001701584700003601601856007101637 2013 d a978-1-4799-0177-700aPrice-based distributed control for networked plug-in electric vehicles0 aPricebased distributed control for networked plugin electric veh aWashington, DCbIEEEc06/2013 a5086 - 50913 aWe introduce a framework for controlling the charging and discharging processes of plug-in electric vehicles (PEVs) via pricing strategies. Our framework consists of a hierarchical decision-making setting with two layers, which we refer to as aggregator layer and retail market layer. In the aggregator layer, there is a set of aggregators that are requested (and will be compensated for) to provide certain amount of energy over a period of time. In the retail market layer, the aggregator offers some price for the energy that PEVs may provide; the objective is to choose a pricing strategy to incentivize the PEVs so as they collectively provide the amount of energy that the aggregator has been asked for. The focus of this paper is on the decision-making process that takes places in the retail market layer, where we assume that each individual PEV is a price-anticipating decision-maker. We cast this decision-making process as a game, and provide conditions on the pricing strategy of the aggregator under which this game has a unique Nash equilibrium. We propose a distributed consensus-based iterative algorithm through which the PEVs can seek for this Nash equilibrium. Numerical simulations are included to illustrate our results.

10aPEVs10areliability and markets10aRM11-0061 aGharesifard, Bahman1 aBasar, Tamer1 aDominguez-Garcia, Alejandro, D. uhttps://certs.lbl.gov/publications/price-based-distributed-control01563nas a2200193 4500008003900000020002200039245006700061210006700128260003300195300001600228520088300244653003901127653002801166653001301194100003601207700002201243700003401265856007001299 2012 d a978-1-4673-2065-800aDecentralized optimal dispatch of distributed energy resources0 aDecentralized optimal dispatch of distributed energy resources aMaui, HI, USAbIEEEc12/2012 a3688 - 36933 aIn this paper, we address the problem of optimally dispatching a set of distributed energy resources (DERs) without relying on a centralized decision maker. We consider a scenario where each DER can provide a certain resource (e.g., active or reactive power) at some cost (namely, quadratic in the amount of resource), with the additional constraint that the amount of resource that each DER provides is upper and lower bounded by its capacity limits. We propose a low-complexity iterative algorithm for DER optimal dispatch that relies, at each iteration, on simple computations using local information acquired through exchange of information with neighboring DERs. We show convergence of the proposed algorithm to the (unique) optimal solution of the DER dispatch problem. We also describe a wireless testbed we developed for testing the performance of the algorithms.

10adistributed energy resources (der)10areliability and markets10aRM11-0061 aDominguez-Garcia, Alejandro, D.1 aCady, Stanton, T.1 aHadjicostis, Christoforos, N. uhttps://certs.lbl.gov/publications/decentralized-optimal-dispatch02310nas a2200253 4500008003900000020002200039245005400061210005300115260003200168300001600200520149400216653003901710653000901749653002701758653001301785653003801798100002301836700002301859700003601882700002501918700002201943700002001965856007101985 2012 d a978-1-4577-1095-700aReal-time scheduling of deferrable electric loads0 aRealtime scheduling of deferrable electric loads aMontreal, QCbIEEEc06/2012 a3643 - 36503 aWe consider a collection of distributed energy resources [DERs] such as electric vehicles and thermostatically controlled loads. These resources are flexible: they require delivery of a certain total energy over a specified service interval. This flexibility can facilitate the integration of renewable generation by absorbing variability, and reducing the reserve capacity and reserve energy requirements. We first model the energy needs of these resources as tasks, parameterized by arrival time, departure time, energy requirement, and maximum allowable servicing power. We consider the problem of servicing these resources by allocating available power using real-time scheduling policies. The available generation consists of a mix of renewable energy [from utility-scale wind-farms or distributed rooftop photovoltaics], and load-following reserves. Reserve capacity is purchased in advance, but reserve energy use must be scheduled in real-time to meet the energy requirements of the resources. We show that there does not exist a causal optimal scheduling policy that respects servicing power constraints. We then present three heuristic causal scheduling policies: Earliest Deadline First [EDF], Least Laxity First [LLF], and Receding Horizon Control [RHC]. We show that EDF is optimal in the absence of power constraints. We explore, via simulation studies, the performance of these three scheduling policies in the metrics of required reserve energy and reserve capacity.

10adistributed energy resources (der)10aPEVs10arenewables integration10aRM11-00610aThermostatically controlled loads1 aSubramanian, Anand1 aGarcia, Manuel, J.1 aDominguez-Garcia, Alejandro, D.1 aCallaway, Duncan, S.1 aPoolla, Kameshwar1 aVaraiya, Pravin uhttps://certs.lbl.gov/publications/real-time-scheduling-deferrable