Multi-time interval power system state estimation incorporating phasor measurements

Guo, Ye; Zhang, Boming; Wu, Wenchuan; Sun, Hongbin

doi:10.1109/pesgm.2015.7286640

Cited by 10 publications

(6 citation statements)

References 17 publications

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“…It is worth noting that when the states are the voltages expressed in rectangular coordinates and PMU measurements are used, SE can be performed efficiently by (linear) weighted least squares or the Kalman filter, whose performance is thoroughly analyzed in [28]. Depending on the variability of power injections, it is also possible to partition the network into three areas, i.e., steady, quasi-steady, and fluctuant, and perform a multi-time scale SE [34].…”

Section: Introductionmentioning

confidence: 99%

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Risbud

Gatsis

Taha

2020

Journal of Modern Power Systems and Clean Energy

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This paper introduces a dynamic network model together with a phasor measurement unit (PMU) measurement model suitable for power system state estimation under spoofing attacks on the global positioning system (GPS) receivers of PMUs. The spoofing attacks may introduce time-varying phase offsets in the affected PMU measurements. An algorithm is developed to jointly estimate the state of the network, which amounts to the nodal voltages in rectangular coordinates, as well as the time-varying attacks. The algorithm features closedform updates. The effectiveness of the algorithm is verified on the standard IEEE transmission networks. It is numerically shown that the estimation performance is improved when the dynamic network model is accounted for compared with a previously reported static approach.

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Section: Introductionmentioning

confidence: 99%

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Risbud

Gatsis

Taha

2020

Journal of Modern Power Systems and Clean Energy

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“…In Reference 21, power system state estimation is first performed by RTU (remote terminal unit) measurements only, deem its state estimates as pseudo‐measurements, and estimate the final states with these pseudo‐measurements along with PMUs via linear estimation. A multi‐time interval state estimation method is proposed in Reference 22. In the article, power networks are partitioned to the steady area, quasi‐steady area, and fluctuant area.…”

Section: Introductionmentioning

confidence: 99%

Data mining based excitation system parameters estimation considering DCS and PMU measurements using cubature Kalman filter

Mohseni

Doroudi

Karrari

2020

Int Trans Electr Energ Syst

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Summary The excitation system is an important system of power plants, which has an effective role in power system dynamic and stability. Consequently, developing an approach for the excitation system's model and parameter estimation is a necessary research goal. In real situations, it is often needed to identify and estimate unknown parameters of the excitation system by field recorded signals. The recorded signal can be internal from the distributed control system (DCS) or external from the phasor measurement unit (PMU). In this article, a novel method based on cubature Kalman filter and data mining is proposed to identify the parameters of a standard type excitation system. Firstly, the best available signals for parameters estimation are chosen. Secondly, a method is proposed to parameters estimation of excitation systems efficiently, when both the DCS and PMU with different sample rates are employed to record the measurement data. Data mining is performed at intervals that DCS data is missing (or unavailable), while PMU data is available. Experimental data are used for validation of the proposed approach.

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“…State estimators using both unsynchronized conventional measurements and synchronized phasor measurements are called hybrid state estimation (HSE) and can be classified into two major categories: one‐phase and two‐phase SEs . In the first category, the SE jointly processes both SCADA and PMU measurements, while in the second category, SCADA and PMU data are processed by separate SE modules . In terms of accuracy, one‐phase state estimators outperform two‐phase ones, because they permit to spread benefits of phasor measurements in all buses …”

Section: Introductionmentioning

confidence: 99%

“…19 In the first category, the SE jointly processes both SCADA and PMU measurements, [19][20][21][22][23][24][25][26][27][28][29] while in the second category, SCADA and PMU data are processed by separate SE modules. 18,19,[30][31][32][33][34][35][36][37][38][39] In terms of accuracy, one-phase state estimators outperform two-phase ones, because they permit to spread benefits of phasor measurements in all buses. 28 In this paper, a new SE framework is proposed for processing RTU and PMU measurements separately in order to leave the traditional weighted least square (WLS)-based SE software unchanged.…”

mentioning

confidence: 99%

A hybrid power system state estimator using synchronized and unsynchronized sensors

Manousakis

Korres

2018

Int Trans Electr Energ Syst

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Summary This paper presents a hybrid state estimator based on measured data delivered by unsynchronized and synchronized sensors, taking into account their different refresh rates. The proposed algorithm is based on a reference‐free problem formulation, using Cartesian coordinates for both the phasorial measurements and the state vector. Each time that supervisory control and data acquisition measurements are updated, a nonlinear state estimator runs using asynchronously gathered measurements and a limited number of synchronized measurements. In between supervisory control and data acquisition scans, each time that phasor measurements are refreshed, a linear state estimation is executed. The proposed scheme processes separately the conventional and the phasorial measurements. The method is validated by simulation results on the IEEE 14 and 118 bus benchmark systems.

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Multi-time interval power system state estimation incorporating phasor measurements

Cited by 10 publications

References 17 publications

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Multi-period Power System State Estimation with PMUs Under GPS Spoofing Attacks

Data mining based excitation system parameters estimation considering DCS and PMU measurements using cubature Kalman filter

A hybrid power system state estimator using synchronized and unsynchronized sensors

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