A Robust PMU Based Three-Phase State Estimator Using Modal Decoupling

Göl, Murat; Abur, Ali

doi:10.1109/tpwrs.2014.2299756

Cited by 69 publications

(31 citation statements)

References 23 publications

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“…As the individual states are uncorrelated [12], and , i.e., both of them are scalar. Typical values of these two quantities for field data were found to be in the order of .…”

Section: A Filteringmentioning

confidence: 99%

Methodology for Performing Synchrophasor Data Conditioning and Validation

Jones

Pal

Thorp

2015

IEEE Trans. Power Syst.

116

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A phasor measurement unit (PMU) only state estimator is intrinsically superior to its SCADA analogue with respect to speed, performance, and reliability. However, ensuring the quality of the data stream which enters the linear estimator is crucial before establishing it as the front end of an EMS or other network applications. One approach is to pre-process the phasor data before it arrives at the linear estimator. This paper presents an algorithm for synchrophasor data conditioning and repair that fits neatly as a prefix into the existing linear state estimation formulation. The methodology has been tested using field data obtained from PMUs installed in Dominion Virginia Power's (DVP's) EHV network. The results indicate that the proposed technique provides a computationally simple, elegant solution to the synchrophasor data quality problem.Index Terms-Data quality, Kalman filter, phasor measurement unit (PMU), state estimation.

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“…As the individual states are uncorrelated [12], and , i.e., both of them are scalar. Typical values of these two quantities for field data were found to be in the order of .…”

Section: A Filteringmentioning

confidence: 99%

Methodology for Performing Synchrophasor Data Conditioning and Validation

Jones

Pal

Thorp

2015

IEEE Trans. Power Syst.

116

View full text Add to dashboard Cite

show abstract

“…Even though PMUs can result in measurements with higher accuracy, the PSSE still constitutes a major challenge due to the presence of bad data or outliers [3,4,5]. Such outliers that are far away from the expected measuring data create the potential risk of misleading the estimated result [6].…”

Section: Introductionmentioning

confidence: 99%

“…However, the algorithm is basically solving a centralized state estimation problem for the distribution system. In [3,4], the least absolute value (LAV) has been proposed to handle the outliers where the measurements are collected from PMUs. However, the algorithms described so far are mostly based on the measurement model only.…”

Section: Introductionmentioning

confidence: 99%

Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems

Chen

Foo

Ling

et al. 2017

Sensors

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In this paper, a distributed state estimation method based on moving horizon estimation (MHE) is proposed for the large-scale power system state estimation. The proposed method partitions the power systems into several local areas with non-overlapping states. Unlike the centralized approach where all measurements are sent to a processing center, the proposed method distributes the state estimation task to the local processing centers where local measurements are collected. Inspired by the partitioned moving horizon estimation (PMHE) algorithm, each local area solves a smaller optimization problem to estimate its own local states by using local measurements and estimated results from its neighboring areas. In contrast with PMHE, the error from the process model is ignored in our method. The proposed modified PMHE (mPMHE) approach can also take constraints on states into account during the optimization process such that the influence of the outliers can be further mitigated. Simulation results on the IEEE 14-bus and 118-bus systems verify that our method achieves comparable state estimation accuracy but with a significant reduction in the overall computation load.

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“…Authors in [11][12][13] have formulated the conventional state estimator problem as the linear weighed least square (WLS) problem or the mixed-integer programming problem. Nevertheless, such state estimators have not been integrated and implemented in a real power system, and it will have high computational cost to implement in large-scale power systems [14]. As a common practice in utilities for critical infrastructures, one or more backup EMSs are typically deployed.…”

Section: Introductionmentioning

confidence: 99%

“…However, this feature requires having current measurement at each of circuit breakers in a substation, which is not realistic with the present coverage of PMU installation. A three phase state estimator using modal decoupling is proposed in [14]. In order to make the least absolute value (LAV) estimator robust to leveraged measurements, system model may need to be modified with virtual buses.…”

Section: Introductionmentioning

confidence: 99%

Synchrophasor-based real-time state estimation and situational awareness system for power system operation

Chen

Zhang

et al. 2016

J. Mod. Power Syst. Clean Energy

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State estimation is a critical functionality of energy management system (EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies, and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable. The unreliable results further impact downstream network and market applications, such as contingency analysis, voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas (ERCOT) and Los Angeles Department of Water and Power (LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.

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A Robust PMU Based Three-Phase State Estimator Using Modal Decoupling

Cited by 69 publications

References 23 publications

Methodology for Performing Synchrophasor Data Conditioning and Validation

Methodology for Performing Synchrophasor Data Conditioning and Validation

Distributed State Estimation Using a Modified Partitioned Moving Horizon Strategy for Power Systems

Synchrophasor-based real-time state estimation and situational awareness system for power system operation

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