A generalized subspace least mean square method is presented for accurate and robust estimation of oscillation modes from exponentially damped power system signals. The method is based on the orthogonality of signal and noise eigenvectors of the signal autocorrelation matrix. Performance of the proposed method is evaluated using Monte Carlo simulation and compared with the Prony method. Test results show that the generalized subspace least mean square method is highly resilient to noise and significantly dominates the Prony method in tracking power system modes under noisy environments.

10aAA09-00210aAARD10aAutomatic Switchable Network (ASN)10aoscillations1 aZhang, Peng1 aZhou, Ning1 aAbdollahi, Ali uhttps://certs.lbl.gov/publications/generalized-subspace-least-mean02020nas a2200253 4500008003900000022001400039245008400053210006900137260001200206300001400218490000700232520124900239653001301488653000901501653003901510653003601549653001801585100001701603700001501620700002101635700001801656700002001674856007201694 2013 d a0885-895000aMode shape estimation algorithms under ambient conditions: A comparative review0 aMode shape estimation algorithms under ambient conditions A comp c05/2013 a779 - 7870 v283 aThis paper provides a comparative review of five existing ambient electromechanical mode shape estimation algorithms, i.e., the Transfer Function (TF), Spectral, Frequency Domain Decomposition (FDD), Channel Matching, and Subspace Methods. It is also shown that the TF Method is a general approach to estimating mode shape and that the Spectral, FDD, and Channel Matching Methods are actually special cases of it. Additionally, some of the variations of the Subspace Method are reviewed and the Numerical algorithm for Subspace State Space System IDentification (N4SID) is implemented. The five algorithms are then compared using data simulated from a 17-machine model of the Western Electricity Coordinating Council (WECC) under ambient conditions with both low and high damping, as well as during the case where ambient data is disrupted by an oscillatory ringdown. The performance of the algorithms is compared using the statistics from Monte Carlo simulations and results from measured WECC data, and a discussion of the practical issues surrounding their implementation, including cases where power system probing is an option, is provided. The paper concludes with some recommendations as to the appropriate use of the various techniques.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10apower systems1 aDosiek, Luke1 aZhou, Ning1 aPierre, John, W.1 aHuang, Zhenyu1 aTrudnowski, Dan uhttps://certs.lbl.gov/publications/mode-shape-estimation-algorithms01443nas a2200217 4500008003900000022001400039245007100053210006700124260001200191300001600203490000700219520077600226653001301002653003901015653001001054653002601064100001401090700002401104700002001128856007701148 2013 d a0885-895000aA Numerical Solver Design for Extended-Term Time-Domain Simulation0 aNumerical Solver Design for ExtendedTerm TimeDomain Simulation c11/2013 a4926 - 49350 v283 aNumerical methods play an important role in improving efficiency for power system time-domain simulation. Motivated by the need to perform high-speed extended-term time-domain simulation (HSET-TDS) for online purposes, this paper presents design principles for numerical solvers of differential algebraic systems associated with power system time-domain simulation, focusing on DAE construction strategies, integration methods, nonlinear solvers, and linear solvers. We have implemented a design appropriate for HSET-TDS, and we have compared the proposed integration method, Hammer-Hollingsworth 4 (HH4), with Trapezoidal rule in terms of computational efficiency and accuracy, using the New England 39-bus system, an expanded 8775-bus system, and PJM 13 029-bus system.10aAA09-00110aAutomatic Switchable Network (ASN)10aRTGRM10aSystem Security Tools1 aFu, Chuan1 aMcCalley, James, D.1 aTong, Jianzhong uhttps://certs.lbl.gov/publications/numerical-solver-design-extended-term01617nas 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-system02044nas a2200217 4500008003900000022001300039245011400052210006900166260001200235300001100247490000800258520133100266653001301597653003901610653001001649653002601659100003101685700002401716700001701740856006901757 2013 d a0378779600aProactive task scheduling and stealing in master-slave based load balancing for parallel contingency analysis0 aProactive task scheduling and stealing in masterslave based load c10/2013 a9 - 150 v1033 aWith increasing emphasis on analyzing N − k contingencies, use of parallel resources has become imperative. Parallelization imposes the requirement of load-balancing for achieving high resource usage efficiency. Conventional static allocation based scheduling techniques fail to achieve load balancing. To address this limitation, master-slave scheduling (MSS) has been used; however, in MSS, after task completion, slave processors wait for the next task to arrive leading to idle-wait. In the case of contention at master, the idle-wait could become significant and degrade the performance of the MSS algorithm. We present a technique to combine the advantage of proactive task scheduling and stealing with the simplicity of MSS. We refer to it as PTMSS. In PTMSS, master proactively queues an extra task at the slave processor, such that on completion of a task, the next task is immediately started. Further, when master runs out of the tasks, it steals a queued task from one slave and allocates to another slave which has completed its tasks. Simulation experiments have been conducted on a large power system with 13,029 buses and thousands of contingencies have been analyzed. The results show that PTMSS performs better than conventional MSS and also offers significant computational gains over serial execution.10aAA09-00110aAutomatic Switchable Network (ASN)10aRTGRM10aSystem Security Tools1 aKhaitan, Siddhartha, Kumar1 aMcCalley, James, D.1 aSomani, Arun uhttps://certs.lbl.gov/publications/proactive-task-scheduling-and01702nas a2200277 4500008003900000022001400039245008200053210006900135260001200204300001600216490000700232520083800239653001301077653000901090653003901099653003601138653002601174653002601200100001301226700002201239700001901261700002301280700002301303700002201326856007601348 2012 d a0885-895000aThe Characteristic Ellipsoid Methodology and its Application in Power Systems0 aCharacteristic Ellipsoid Methodology and its Application in Powe c11/2012 a2206 - 22140 v273 aThe characteristic ellipsoid (CELL) method to monitor dynamic behaviors of a power system is proposed. Multi-dimensional minimum-volume-enclosing characteristic ellipsoids are built using synchronized phasor measurements. System dynamic behaviors are identified by tracking the change rate of the CELL's characteristic indices. Decision tree techniques are used to link the CELL's characteristic indices and the system's dynamic behaviors and to determine types, locations and related information about the dynamic behaviors. The knowledge base of representative transient events is created by offline simulations based on the full Western Electric Coordinating Council (WECC) model. Two case studies demonstrate that the CELL method combined with the decision trees can detect transient events and their features with good accuracy.10aAA07-00210aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10aPower system dynamics10asituational awareness1 aMa, Jian1 aMakarov, Yuri, V.1 aDiao, Ruisheng1 aEtingov, Pavel, V.1 aDagle, Jeffery, E.1 aDe Tuglie, Enrico uhttps://certs.lbl.gov/publications/characteristic-ellipsoid-methodology01837nas a2200241 4500008003900000022001400039245008100053210006900134260001200203300001600215490000700231520109000238653001301328653000901341653003901350653003601389653002701425653001001452100001501462700002101477700002001498856007701518 2012 d a0885-895000aA Stepwise Regression Method for Estimating Dominant Electromechanical Modes0 aStepwise Regression Method for Estimating Dominant Electromechan c05/2012 a1051 - 10590 v273 aProny analysis has been applied to estimate inter-area oscillation modes using phasor measurement unit (PMU) measurements. To suppress noise and signal offset effects, a high-order Prony model usually is used to over-fit the data. As such, some trivial modes are intentionally added to improve the estimation accuracy of the dominant modes. Therefore, to reduce the rate of false alarms, it is important to distinguish between the dominant modes that reflect the dynamic features of a power system and the trivial modes that are artificially introduced to improve the estimation accuracy. In this paper, a stepwise-regression method is applied to automatically identify the dominant modes from Prony analysis. A Monte Carlo method is applied to evaluate the performance of the proposed method using data obtained from simulations. Field-measured PMU data are used to verify the applicability of the proposed method. A comparison of results obtained using the proposed approach with results from a traditional energy-sorting method shows the improved performance of the proposed method.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10aPower system stability10aRTGRM1 aZhou, Ning1 aPierre, John, W.1 aTrudnowski, Dan uhttps://certs.lbl.gov/publications/stepwise-regression-method-estimating01513nas a2200217 4500008003900000020002200039245007900061210006900140260003500209300001000244520080700254653001301061653000901074653003901083653001801122653002801140100001601168700001501184700002101199856007501220 2011 d a978-1-4577-0417-800aEvaluation of mode estimation accuracy for small-signal stability analysis0 aEvaluation of mode estimation accuracy for smallsignal stability aBoston, MA, USAbIEEEc08/2011 a1 - 73 aThis paper proposes a method for determining electromechanical mode estimate accuracy by relating mode estimate error to residual values. Mode frequency and damping ratio were estimated using Prony analysis and residuals were calculated for a 17-machine model with varying levels of load noise. Mode estimate error and residuals were found to increase proportionally to each other as noise values were increased, revealing a distinctly linear relationship. The use of these results to develop appropriate confidence in models is discussed. With the relationship established, a method of predicting mode estimate error values based on residuals in the western North American power system (wNAPS) was developed. The potential of this method to evaluate the confidence level of mode estimates is examined.10aAA09-00210aAARD10aAutomatic Switchable Network (ASN)10aload modeling10apower system monitoring1 aFollum, Jim1 aZhou, Ning1 aPierre, John, W. uhttps://certs.lbl.gov/publications/evaluation-mode-estimation-accuracy02070nas a2200277 4500008003900000020002200039245008600061210006900147260003600216300001000252520120300262653001301465653000901478653003901487653001201526653002601538653002701564653000901591100001601600700002201616700001901638700001501657700001801672700002501690856007701715 2011 d a978-1-4577-1000-100aThe influence of topology changes on inter-area oscillation modes and mode shapes0 ainfluence of topology changes on interarea oscillation modes and aDetroit, MI, USAbIEEEc07/2011 a1 - 73 aThe topology of a power grid network is a piece of critical information for power grid operations. Different power grid topologies can change grid characteristics, inter-area oscillation modes, mode shapes, and even the robustness of the power system. This paper presents some preliminary study results, based on an approved WECC operating case and a modified low damping WECC system, to show the impact of topology changes resulting from N-1 contingencies on power system modes and mode shapes. The results show that topology changes can have very different impact on modal properties in a power system: some result in an unstable situation, while others can improve small signal stability. For the former, the studies show about a 4.5% damping reduction, so a 5% damping margin would be required to ensure the system can sustain the contingencies. For the latter, those topology changes could be used as a control method to improve small signal stability. Mode shapes normally do not change when there is an N-1 topology change. These observations suggest that the inclusion of topological information is useful for improving the accuracy and effectiveness of power system control schemes.

10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10adamping10apower grid operations10aPower system stability10aWECC1 aChen, Yousu1 aFuller, Jason, C.1 aDiao, Ruisheng1 aZhou, Ning1 aHuang, Zhenyu1 aTuffner, Francis, K. uhttps://certs.lbl.gov/publications/influence-topology-changes-inter-area01571nas a2200241 4500008003900000020002200039245008200061210006900143260003600212300001000248520076300258653001301021653000901034653003901043653003601082653002901118100001501147700001801162700002501180700002001205700002901225856007501254 2011 d a978-1-4577-1000-100aA modified stepwise linear regression method for estimating modal sensitivity0 amodified stepwise linear regression method for estimating modal aDetroit, MI, USAbIEEEc07/2011 a1 - 73 aSmall signal stability problems are one of the major threats to grid stability and reliability. Low damping of inter area modes is usually considered to be a result of heavy power transfer over long distances. This paper proposes a modified stepwise regression method to estimate the modal sensitivity with respect to power flow on the transmission lines based on measurement. This sensitivity is used to identify dominant transmission lines, whose power flow has significant influence on the inter-area modal damping. It is shown through simulation study that the proposed method can effectively estimate the modal sensitivity with respect to line power flow. This, in turn, provides insight on how to improve damping through adjusting tie line flow.

10aAA09-00210aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10apower system reliability1 aZhou, Ning1 aHuang, Zhenyu1 aTuffner, Francis, K.1 aTrudnowski, Dan1 aMittelstadt, William, A. uhttps://certs.lbl.gov/publications/modified-stepwise-linear-regression02010nas a2200229 4500008003900000022001400039245007400053210007100127260001200198300001200210490000700222520131900229653001301548653000901561653003901570653003601609653001501645100001401660700001701674700001601691856007301707 2011 d a0885-895000aTransition to a Two-Level Linear State Estimator—Part II: Algorithm0 aTransition to a TwoLevel Linear State Estimator—Part II Algorith c02/2011 a54 - 620 v263 aThe availability of synchro-phasor data has raised the possibility of a linear state estimator if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. Moreover, the new digital substations can perform some of the computation at the substation itself resulting in a more accurate two-level state estimator. The main contribution in this paper is that this two-level processing removes the bad data and topology errors, which are major problems today, at the substation level. In Part I of the paper, we describe the layered architecture of databases, communications, and the application programs that are required to support this two-level linear state estimator. In Part II, we describe the mathematical algorithms that are different from those in the existing literature. As the availability of phasor measurements at substations will increase gradually, this paper describes how the state estimator can be enhanced to handle both the traditional state estimator and the proposed linear state estimator simultaneously. This provides a way to immediately utilize the benefits in those parts of the system where such phasor measurements become available and provides a pathway to transition to the "smart" grid of the future.10aAA05-00210aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10asmart grid1 aYang, Tao1 aSun, Hongbin1 aBose, Anjan uhttps://certs.lbl.gov/publications/transition-two-level-linear-state01950nas a2200265 4500008003900000020002200039245009000061210006900151260002900220300001000249520110800259653001301367653000901380653003901389653001201428653001701440653002501457653002601482653002701508100001801535700001501553700002501568700002001593856007101613 2011 d a978-1-4244-9618-100aUse of Modal Sensitivity to Operating Conditions for Damping Control in Power Systems0 aUse of Modal Sensitivity to Operating Conditions for Damping Con aKauai, HIbIEEEc01/2011 a1 - 93 aSmall signal stability is an inherent characteristic of dynamic systems such as power systems. Pole positioning through power system stabilizers (PSS) is often used for improving damping in power systems. A well-designed PSS can be very effective in damping oscillations, especially local oscillations. However, designing PSSs for inter-area oscillations has been a very challenging task due to time-varying operating conditions affecting the oscillations. This paper explores the sensitivity relationship between oscillations and operating conditions, and employs the relationship to derive recommendations for operator's actions to adjust operating conditions for improving damping. Low damping is usually considered to be a result of heavy power transfer in long distance, while specific locations also have significant impact on damping of oscillations. Therefore, it is important to consider locations in deriving recommendations. This paper proposes the concept of relative modal sensitivity and presents its application in deriving recommendations for operator's action in damping control.

10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10adamping10aoscillations10apower system control10aPower system dynamics10aPower system stability1 aHuang, Zhenyu1 aZhou, Ning1 aTuffner, Francis, K.1 aTrudnowski, Dan uhttps://certs.lbl.gov/publications/use-modal-sensitivity-operating01760nas a2200253 4500008003900000020002200039245011400061210006900175260003500244300001000279520090000289653001301189653000901202653003901211653002101250653003601271653002801307100001501335700001801350700002501368700002101393700002201414856007001436 2010 d a978-1-4244-6549-100aAutomatic implementation of Prony analysis for electromechanical mode identification from phasor measurements0 aAutomatic implementation of Prony analysis for electromechanical aMinneapolis, MNbIEEEc07/2010 a1 - 83 aSmall signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and propose an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps to guarantee that Prony analysis is properly and timely applied on the ringdown data. Thus, the mode estimation results can be performed reliably and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis.

10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10agrid reliability10aphasor measurement units (PMUs)10apower system monitoring1 aZhou, Ning1 aHuang, Zhenyu1 aTuffner, Francis, K.1 aPierre, John, W.1 aJin, Shuangshuang uhttps://certs.lbl.gov/publications/automatic-implementation-prony01447nas a2200241 4500008003900000022001400039245009800053210006900151260001200220300001600232490000700248520068700255653001300942653000900955653003900964653001001003653002601013653002901039653001001068100003101078700002401109856007201133 2010 d a0885-895000aA Class of New Preconditioners for Linear Solvers Used in Power System Time-Domain Simulation0 aClass of New Preconditioners for Linear Solvers Used in Power Sy c11/2010 a1835 - 18440 v253 aIn this paper, a new class of preconditioners for iterative methods is proposed for the solution of linear equations that arise in the time-domain simulation of the power system. The system of linear equations results from an attempt to solve the differential algebraic equations (DAE) encountered in the power system dynamic simulation. The preconditioners are based on the multifrontal direct methods. The proposed method is compared to the incomplete LU factorization (ILU) based preconditioned iterative methods and other conventional direct linear sparse solvers. The comparison shows the proposed method achieves great computational efficiency relative to these other methods.10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aCERTS10aPower system modeling10apower system reliability10aRTGRM1 aKhaitan, Siddhartha, Kumar1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/class-new-preconditioners-linear01121nas a2200205 4500008003900000022001400039245006300053210006100116260001200177300001400189490000700203520051100210653000900721653003900730653001400769653001300783100001900796700002300815856007700838 2010 d a0885-895000aFast Newton-FGMRES Solver for Large-Scale Power Flow Study0 aFast NewtonFGMRES Solver for LargeScale Power Flow Study c05/2010 a769 - 7760 v253 aA fast Newton-FGMRES method for power flow calculations is proposed in this paper. Three accelerating schemes to speed up the Newton-FGMRES method are proposed. Numerical studies show that the proposed fast Newton-FGMRES method consistently outperforms the traditional Newton-GMRES method and Newton-LU method on two practical power systems-one with 12 000 buses, another with 21 000 buses. For the 21 000-bus system, the fast Newton-FGMRES method can be 45.7% faster than the traditional Newton-LU method.10aAARD10aAutomatic Switchable Network (ASN)10aload flow10aRM11-0081 aZhang, Yi-Shan1 aChiang, Hsiao-Dong uhttps://certs.lbl.gov/publications/fast-newton-fgmres-solver-large-scale02029nas a2200277 4500008003900000020002200039245007200061210006900133260003500202300001000237520114200247653001301389653000901402653003901411653003601450653002701486100001801513700001501531700002501546700001601571700002001587700002901607700002001636700002301656856007201679 2010 d a978-1-4244-6549-100aImproving small signal stability through operating point adjustment0 aImproving small signal stability through operating point adjustm aMinneapolis, MNbIEEEc07/2010 a1 - 83 aModeMeter techniques for real-time small-signal stability monitoring continue to mature, and more and more phasor measurements are available in power systems. It has come to the stage to bring modal information into real-time power system operation. This paper proposes to establish a procedure for Modal Analysis for Grid Operations (MANGO). Complementary to PSS and other traditional modulation-based control, MANGO aims to provide suggestions such as redispatching generation for operators to mitigate low-frequency oscillations. Load would normally not be reduced except as a last resort. Different from modulation-based control, the MANGO procedure proactively maintains adequate damping at all times, rather than reacting to disturbances when they occur. The effect of operating points on small-signal stability is presented in this paper. Implementation with existing operating procedures is discussed. Several approaches for modal sensitivity estimation are investigated to associate modal damping and operating parameters. The effectiveness of the MANGO procedure is confirmed through simulation studies of several test systems.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10aPower system stability1 aHuang, Zhenyu1 aZhou, Ning1 aTuffner, Francis, K.1 aChen, Yousu1 aTrudnowski, Dan1 aMittelstadt, William, A.1 aHauer, John, F.1 aDagle, Jeffery, E. uhttps://certs.lbl.gov/publications/improving-small-signal-stability01314nas a2200229 4500008003900000020002200039245011100061210006900172260004000241300001000281520052500291653001300816653000900829653003900838653002600877100002500903700001800928700001500946700002500961700002400986856007401010 2010 d a978-1-4244-6546-000aInitial studies on actionable control for improving small signal stability in interconnected power systems0 aInitial studies on actionable control for improving small signal aNew Orleans, LA, USAbIEEEc04/2010 a1 - 63 aPower consumption and demand continues to grow around the world. As the electric power grid continues to be put under more stress, the conditions of instability are more likely to occur. One cause of such instabilities is intearea oscillations, such as the oscillation that resulted in the August 10, 1996 blackout of the WECC. This paper explores different potential operations of different devices on the power system to improve the damping of these interarea oscillations using two different simulation models.

10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aPower system modeling1 aTuffner, Francis, K.1 aHuang, Zhenyu1 aZhou, Ning1 aGuttromson, Ross, T.1 aJayantilal, Avnaesh uhttps://certs.lbl.gov/publications/initial-studies-actionable-control01571nas a2200217 4500008003900000020002200039245012000061210006900181260004100250300001000291520079800301653001301099653000901112653003901121653003001160653003601190100002201226700001401248700002001262856007101282 2010 d a978-1-4244-5509-600aMerging PMU, Operational, and Non-Operational Data for Interpreting Alarms, Locating Faults and Preventing Cascades0 aMerging PMU Operational and NonOperational Data for Interpreting aHonolulu, Hawaii, USAbIEEEc01/2010 a1 - 93 aWith the development of synchronized sampling technique and other advanced measurement approaches, the merging of various substation data to be used in new applications in the EMS solutions has not yet been explored adequately. This paper deals with the integration of time correlated information from Phasor Measurement Units, SCADA and non-operational data captured by other intelligent electronic devices such as protective relays and digital fault recorders, as well as their applications in alarm processing, fault location and cascading event analysis. A set of new control center visualization tools shows that the merging of PMU, operational and non-operational data could improve the effectiveness of alarm processing, accuracy of fault location and ability to detect cascades.

10aAA05-00310aAARD10aAutomatic Switchable Network (ASN)10aenergy management systems10aphasor measurement units (PMUs)1 aKezunovic, Mladen1 aZheng, Ce1 aPang, Chengzong uhttps://certs.lbl.gov/publications/merging-pmu-operational-and-non01982nas a2200205 4500008003900000022001400039245006600053210006500119260001100184300001400195490000600209520134900215653001301564653000901577653003901586100003101625700002401656700002101680856007501701 2010 d a1868-396700aNumerical methods for on-line power system load flow analysis0 aNumerical methods for online power system load flow analysis c8/2010 a273 - 2890 v13 aNewton-Raphson method is the most widely accepted load flow solution algorithm. However LU factorization remains a computationally challenging task to meet the real-time needs of the power system. This paper proposes the application of very fast multifrontal direct linear solvers for solving the linear system sub-problem of power system real-time load flow analysis by utilizing the state-of-the-art algorithms for ordering and preprocessing. Additionally the unsymmetric multifrontal method for LU factorization and highly optimized Intel® Math Kernel Library BLAS has been used. Two state-of-the-art multifrontal algorithms for unsymmetric matrices namely UMFPACK V5.2.0 and sequential MUMPS 4.8.3 (“Multifrontal Massively Parallel Solver”) are customized for the AC power system Newton-Raphson based load flow analysis. The multifrontal solvers are compared against the state-of-the-art sparse Gaussian Elimination based HSL sparse solver MA48. This study evaluates the performance of above multifrontal solvers in terms of number of factors, computational time, number of floating-point operations and memory, in the context of load flow solution on nine systems including very large real power systems. The results of the performance evaluation are reported. The proposed method achieves significant reduction in computational time.10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)1 aKhaitan, Siddhartha, Kumar1 aMcCalley, James, D.1 aRaju, Mandhapati uhttps://certs.lbl.gov/publications/numerical-methods-line-power-system02086nas a2200253 4500008003900000022001400039245005800053210005800111260001200169300001400181490000700195520135600202653001301558653000901571653003901580653000901619100002101628700001501649700002501664700002001689700002001709700002901729856007401758 2010 d a0885-895000aProbing Signal Design for Power System Identification0 aProbing Signal Design for Power System Identification c05/2010 a835 - 8430 v253 aThis paper investigates the design of effective input signals for low-level probing of power systems. In 2005, 2006, and 2008 the Western Electricity Coordinating Council (WECC) conducted four large-scale system-wide tests of the western interconnected power system where probing signals were injected by modulating the control signal at the Celilo end of the Pacific DC intertie. A major objective of these tests is the accurate estimation of the inter-area electromechanical modes. A key aspect of any such test is the design of an effective probing signal that leads to measured outputs rich in information about the modes. This paper specifically studies low-level probing signal design for power-system identification. The paper describes the design methodology and the advantages of this new probing signal which was successfully applied during these tests. This probing input is a multi-sine signal with its frequency content focused in the range of the inter-area modes. The period of the signal is over 2 min providing high-frequency resolution. Up to 15 cycles of the signal are injected resulting in a processing gain of 15. The resulting system response is studied in the time and frequency domains. Because of the new probing signal characteristics, these results show significant improvement in the output SNR compared to previous tests.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aWECC1 aPierre, John, W.1 aZhou, Ning1 aTuffner, Francis, K.1 aHauer, John, F.1 aTrudnowski, Dan1 aMittelstadt, William, A. uhttps://certs.lbl.gov/publications/probing-signal-design-power-system01873nas a2200253 4500008003900000020002200039245008000061210006900141260003600210300001000246520106600256653001301322653000901335653003901344653002701383653003601410100001901446700001801465700001301483700002001496700001501516700001501531856007301546 2009 d a978-1-4244-3810-500aDecision tree assisted controlled islanding for preventing cascading events0 aDecision tree assisted controlled islanding for preventing casca aSeattle, WA, USAbIEEEc03/2009 a1 - 83 aAt stressed operating conditions, critical contingencies can initiate loss of synchronism and trigger cascading events. Controlled islanding is the last line of defense to stabilize the whole system. This paper presents a decision tree assisted scheme to determine the timing of controlled islanding in real time by using phasor measurements. In addition, a slow coherency based approach is used to determine where to island. This scheme is tested on the operational model of the Entergy system and a severe N-2 outage case is used to demonstrate the phenomenon of cascading events due to protective relay actions. The results show that training one decision tree only for a specified critical contingency that can potentially cause cascading events can yields high prediction accuracy. Being aware of loss of synchronism in real time, operators can implement controlled islanding at carefully designed transmission interfaces and rapidly stabilize each island. Thus a significant amount of load is still served compared to uncontrolled system islanding.

10aAA05-00110aAARD10aAutomatic Switchable Network (ASN)10adistributed generation10aphasor measurement units (PMUs)1 aDiao, Ruisheng1 aVittal, Vijay1 aSun, Kai1 aKolluri, Sharma1 aMandal, S.1 aGalvan, F. uhttps://certs.lbl.gov/publications/decision-tree-assisted-controlled01776nas a2200241 4500008003900000020002200039245010900061210006900170260003500239300001000274520096800284653001301252653000901265653003901274653003601313653002601349100001501375700001801390700001701408700002001425700002101445856006801466 2009 d a978-1-4244-4241-600aElectromechanical mode shape estimation based on transfer function identification using PMU measurements0 aElectromechanical mode shape estimation based on transfer functi aCalgary, CanadabIEEEc07/2009 a1 - 73 aPower system mode shapes are a key indication of how dynamic components participate in low-frequency oscillations. Traditionally, mode shapes are calculated from a linearized dynamic model. For large-scale power systems, obtaining accurate dynamic models is very difficult. Therefore, measurement-based mode shape estimation methods have certain advantages, especially for the application of real-time small signal stability monitoring. In this paper, a measurement-based mode shape identification method is proposed. The general relationship between transfer function (TF) and mode shape is derived. As an example, a least square (LS) method is implemented to estimate mode shape using an autoregressive exogenous (ARX) model. The performance of the proposed method is evaluated by Monte-Carlo studies using simulation data from a 17-machine model. The results indicate the validity of the proposed method in estimating mode shapes with reasonably good accuracy.10aAA07-00110aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10aPower system modeling1 aZhou, Ning1 aHuang, Zhenyu1 aDosiek, Luke1 aTrudnowski, Dan1 aPierre, John, W. uhttps://certs.lbl.gov/publications/electromechanical-mode-shape01597nas a2200241 4500008003900000022001400039245008500053210006900138260001200207300001400219490000700233520087500240653001301115653000901128653003901137653001001176100002001186700002001206700002201226700001701248700001601265856007401281 2009 d a0885-897700aGridStat: A Flexible QoS-Managed Data Dissemination Framework for the Power Grid0 aGridStat A Flexible QoSManaged Data Dissemination Framework for c01/2009 a136 - 1430 v243 aWith the increase in the monitoring of operational data at very high rates in high voltage substations and the ability to time synchronize these data with global positioning systems, there is a growing need for transmitting this data for monitoring, operation, protection, and control needs. The sets of data that need to be transferred and the speed at which they need to be transferred depend on the application-for example, slow for postevent analysis, near real time for monitoring and as close to real time as possible for control or protection. In this paper, we describe GridStat, a novel middleware framework we have developed to provide flexible, robust, and secure data communications for the power grid's operations. Test results demonstrate that such a flexible framework can also guarantee latency that is suitable for fast wide-area protection and control.10aAA05-00210aAARD10aAutomatic Switchable Network (ASN)10aPSERC1 aGjermundrod, H.1 aGjermundrod, H.1 aBakken, David, E.1 aHauser, C.H.1 aBose, Anjan uhttps://certs.lbl.gov/publications/gridstat-flexible-qos-managed-data01718nas a2200241 4500008003900000022001400039245007500053210006900128260001200197300001200209490000700221520100500228653001301233653000901246653003901255653001001294653002601304653001001330653002601340100001401366700002401380856007201404 2009 d a0885-895000aPower System Risk Assessment and Control in a Multiobjective Framework0 aPower System Risk Assessment and Control in a Multiobjective Fra c02/2009 a78 - 850 v243 aTraditional online security assessment determines whether the system is secure or not, but how secure or insecure is not explicitly indicated. This paper develops probabilistic indices, risk, to assess real-time power system security level. Risk captures not only event likelihood, but also consequence. System security level associated with low voltage and overload can be optimally controlled, using the NSGA multiobjective optimization method. A security diagram is used to visualize operating conditions in a way that enables both risk-based and traditional deterministic views. An index for cascading overloads is used to evaluate the Pareto optimal solutions. This paper shows that the multiobjective approach results in less risky and less costly operating conditions, and it provides a practical algorithm for implementation. The IEEE 24-bus RTS-1996 system is analyzed to show that risk-based system security control results in lower risk, lower cost, and less exposure to cascading outages.10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aCERTS10apower system security10aRTGRM10aSystem Security Tools1 aXiao, Fei1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/power-system-risk-assessment-and01848nas a2200229 4500008003900000020002200039245012200061210006900183260003600252300001000288520104800298653001301346653000901359653003901368653002501407653002401432653002601456653002701482100001801509700002201527856006901549 2009 d a978-1-4244-3810-500aThe problem of initiating controlled islanding of a large interconnected power system solved as a Pareto optimization0 aproblem of initiating controlled islanding of a large interconne aSeattle, WA, USAbIEEEc03/2009 a1 - 73 aControlled islanding of a large electric power system is proposed under rare circumstances as a measure of last resort to avoid a catastrophic blackout. Controlled islanding appears to be more desirable than uncontrolled islanding. A separate power system operating objective is the retention of synchronous operation of the entire system to ensure the viability of power markets. The problem of when to initiate controlled islanding, accounting for power marketing objectives is formulated as a multiobjective optimization. Pareto optimization is applied in the form of the calculation of a Pareto surface. This formulation may allow power system operators to manage the multiobjectives of mitigating the possibility of a blackout versus the full enabling of power markets. This is a conceptual paper in which the analytical basis and the main points of the solution of when to initiate controlled islanding are outlined. The objective function recommended for the capture of transient stability is the transient stability load margin.

10aAA05-00110aAARD10aAutomatic Switchable Network (ASN)10acontrolled islanding10aelectricity markets10aPower system dynamics10apower system economics1 aVittal, Vijay1 aHeydt, Gerald, T. uhttps://certs.lbl.gov/publications/problem-initiating-controlled01595nas a2200229 4500008003900000020002200039245006100061210006000122260003500182300001000217520086800227653001301095653000901108653003901117653001401156653002901170653002701199653002901226100001301255700002401268856007301292 2009 d a978-1-4244-4241-600aRisk-based optimal power flow and system operation state0 aRiskbased optimal power flow and system operation state aCalgary, CanadabIEEEc07/2009 a1 - 63 aIn this paper, the risk-based optimal power flow is proposed, which minimizes the economic cost considering the system reliability, and a refined system operation state is provided to clarify this approach. In order to obtain better economic benefit than traditional security-constrained optimal power flow, the corrective optimal power flow is used in this work. The reliability is represented by the risk index, which captures the expected impact to the system. This problem is solved by Benders decomposition. The specific designed Benders subproblem will assure that no collapse or cascading overload occurs for the corrective optimal power flow problem. The approach auto-steers the dispatch between different risk level according to the probability and consequence of the upcoming contingency events. Case studies with a six-bus system are presented.

10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aload flow10aoptimal power flow (OPF)10apower system economics10apower system reliability1 aLi, Yuan1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/risk-based-optimal-power-flow-and01531nas a2200217 4500008003900000020002200039245004700061210004500108260003600153300001000189520087300199653001301072653000901085653003901094653003601133653002501169100001401194700001701208700001601225856007201241 2009 d a978-1-4244-3810-500aTwo-level PMU-based linear state estimator0 aTwolevel PMUbased linear state estimator aSeattle, WA, USAbIEEEc03/2009 a1 - 63 aThe State Estimator function in a control center today is a suite of three programs solved sequentially: topology processing, state estimation, and bad data detection-identification. The state estimation equations are nonlinear because the inputs are mostly real and reactive power measurements. A linear state estimator is possible if the inputs are only complex currents and voltages and if there are enough such measurements to meet observability and redundancy requirements. The main contribution in this paper is the suggestion that the topology processing function and the bad data detection-identification be done at each substation rather than at the control center. It is shown how this two-level processing is faster and more accurate leaving the control center level state estimator solution free of the bad data errors that are major problems today.

10aAA05-00210aAARD10aAutomatic Switchable Network (ASN)10aphasor measurement units (PMUs)10apower system control1 aYang, Tao1 aSun, Hongbin1 aBose, Anjan uhttps://certs.lbl.gov/publications/two-level-pmu-based-linear-state01543nas a2200217 4500008003900000022001400039245007100053210006900124260001200193300001600205490000700221520088400228653001301112653000901125653003901134653001701173653002701190100001601217700001601233856007601249 2008 d a0885-895000aDesign of Wide-Area Damping Controllers for Interarea Oscillations0 aDesign of WideArea Damping Controllers for Interarea Oscillation c08/2008 a1136 - 11430 v233 aThis paper develops a systematic procedure of designing a centralized damping control system for power grid interarea oscillations putting emphasis on the signal selection and control system structure assignment. Geometric measures of controllability/observability are used to select the most effective stabilizing signals and control locations. Line power flows and currents are found to be the most effective input signals. The synthesis of the controller is defined as a problem of mixed H 2/H infin output-feedback control with regional pole placement and is resolved by the linear matrix inequality (LMI) approach. A tuning process and nonlinear simulations are then used to modify the controller parameters to ensure the performance and robustness of the controller designed with linear techniques. The design process is tested on the New England 39-bus ten-machine system.10aAA05-00210aAARD10aAutomatic Switchable Network (ASN)10aoscillations10aPower system stability1 aZhang, Yang1 aBose, Anjan uhttps://certs.lbl.gov/publications/design-wide-area-damping-controllers01545nas a2200229 4500008003900000022001400039245007100053210006900124260001200193300001600205490000700221520083200228653001301060653000901073653003901082653002401121653002601145100003101171700002401202700001701226856007201243 2008 d a0885-895000aMultifrontal Solver for Online Power System Time-Domain Simulation0 aMultifrontal Solver for Online Power System TimeDomain Simulatio c11/2008 a1727 - 17370 v233 aThis paper proposes the application of unsymmetric multifrontal method to solve the differential algebraic equations (DAE) encountered in the power system dynamic simulation. The proposed method achieves great computational efficiency as compared to the conventional Gaussian elimination methods and other linear sparse solvers due to the inherent parallel hierarchy present in the multifrontal methods. Multifrontal methods transform or reorganize the task of factorizing a large sparse matrix into a sequence of partial factorization of smaller dense frontal matrices which utilize the efficient Basic linear algebra subprograms 3 (BLAS 3) for dense matrix kernels. The proposed method is compared with the full Gaussian elimination methods and other direct sparse solvers on test systems and the results are reported.

10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10adynamic simulations10aPower system dynamics1 aKhaitan, Siddhartha, Kumar1 aMcCalley, James, D.1 aChen, Qiming uhttps://certs.lbl.gov/publications/multifrontal-solver-online-power01168nas a2200241 4500008003900000022001400039245007800053210006900131260001200200300001600212490000700228520042200235653001300657653000900670653003900679653002900718653002600747653002600773653001800799100001400817700002400831856007100855 2007 d a0885-895000aRisk-Based Security and Economy Tradeoff Analysis for Real-Time Operation0 aRiskBased Security and Economy Tradeoff Analysis for RealTime Op c11/2007 a2287 - 22880 v223 aThis letter describes a new perspective on balancing system security level with cost for real-time operation. Security level is quantified using risk, which provides that security may be optimized. A risk-based multiple-objective (RBMO) model, considering security and economy together, is compared with the traditional security-constrained OPF (SCOPF) model. A six-bus test system is used to show the merits of RBMO.10aAA09-00110aAARD10aAutomatic Switchable Network (ASN)10aoptimal power flow (OPF)10aPower system modeling10apower system security10arisk analysis1 aXiao, Fei1 aMcCalley, James, D. uhttps://certs.lbl.gov/publications/risk-based-security-and-economy