Linear LAV‐based state estimation integrating hybrid SCADA/PMU measurements

Dobakhshari, Ahmad Salehi; Azizi, Sadegh; Abdolmaleki, Mohammad; Terzija, Vladimir

doi:10.1049/iet-gtd.2019.1850

Cited by 31 publications

(14 citation statements)

References 32 publications

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“…In this paper, the feeder system as shown in Figure 6 is adopted to verify the effectiveness of the proposed method. is the measure measured at the i unit at the t time cross section, μt,i is the true value of the tidal current measured at the i unit at the t time cross section, σ 2 t,i is the variance of the measure at the i unit at the t time cross section. For a measurement device with the maximum η error, the true value μt,i the standard deviation of the measure is:…”

Section: ⅴ Case Studymentioning

confidence: 99%

“…It stays radiant during normal operation. When fault occurs or optimal control is implemented, the segmented switch and contact line act, and the topology of the distribution network changes [1], [2]. Due to the problems such as missing and false information in the remote transmission data of distribution network, or even the absence of communication channels at some nodes, manual inspection and reporting are required, which results in the failure of timely update of the network topology stored in the system, thus affecting the safe and economic operation of distribution network [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Zhang¹,

Zhang²,

Li³

et al. 2022

IEEE Access

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Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multiuser data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multiuser fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multiuser data fusion is carried out, and a PMU based multiuser data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multiuser and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective. INDEX TERMS Distribution network,nonsynchronous measurement, multi-prosumer data, topology identification, prosumer gourp.

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Section: ⅴ Case Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Zhang¹,

Zhang²,

Li³

et al. 2022

IEEE Access

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“…In what follows, firstly SCADA measurements used for SE are formulated based on the results from [31], [32]. Next, the derivations corresponding to PMU measurements including the phase-angle measurements and voltage and current phasor measurements are developed.…”

Section: Exact Linear Formulations For Measurementsmentioning

confidence: 99%

“…Since [H H H] in (28) and therefore [M ] is not constant, δ 2 ,...,δ n in (32), which are estimated in (31), are used to transfer all measurements to the right hand side of (31).…”

Section: B Real Formulationmentioning

confidence: 99%

Robust Hybrid Linear State Estimator Utilizing SCADA and PMU Measurements

Dobakhshari

Abdolmaleki

Terzija

et al. 2021

IEEE Trans. Power Syst.

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This paper intends to improve the accuracy of power system State Estimation (SE) by introducing a hybrid linear robust state estimator. To this end, automatic bad data rejection is accomplished through an M-estimator, i.e. a Schweppe-type estimator with Huber loss function. The method of Iteratively Reweighted Least Squares (IRLS) is used to maximize the likelihood function in the M-estimator. Leverage measurements are also treated by a simple yet effective formulation. To run the algorithm for real-world large-scale grids, cumbersome construction of the Jacobian matrix at each iteration is avoided. In addition, convergence to the local minima faced in the largescale Gauss-Newton algorithm is not a concern as the proposed formulation is linear with no approximation. As observability and redundancy considerations mandate SE to take advantage of traditional SCADA measurements along with available PMU measurements, the linearity of the proposed SE formulation is guaranteed regardless of whether PMU-only, SCADA-only or hybrid SCADA/PMU measurements are utilized. In this regard, covariance matrix for measurements weights is derived for both types of measurements. Thanks to the linear formulation and therefore swiftness of the proposed algorithm, SE could be run for different power systems with a few up to thousands of buses.

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“…However, regardless of the established linearity, the structure of the algorithm's optimisation problem still imposes considerable computational burden. A linear LAV‐based hybrid estimator, which builds upon the work in [15], was recently proposed in [22] for systems observed by RTU and PMU measurements. The states are estimated in two stages by solving two LP problems, such that the phase angles are estimated by the first LP, while the second provides the estimates of complex bus voltages.…”

Section: Introductionmentioning

confidence: 99%

Linear state estimation and bad data detection for power systems with RTU and PMU measurements

Jovičić

Hug

2020

IET Generation, Transmission & Distribution

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In this paper, a novel linear algorithm is proposed for state estimation including bad data detection of power systems that are monitored both by conventional and synchrophasor measurements. Both types of data are treated simultaneously and the states are estimated in rectangular coordinates. The proposed estimator is based on the linear weighted least square method. To enable the derivation of linear measurement functions, the network is modelled in terms of voltages and currents in rectangular form and pseudo-measurements are used to represent conventional measurements. Furthermore, the largest normalized residual test is used to detect bad data. To validate the accuracy and robustness of the proposed algorithm, several test cases of different sizes are solved and the results are presented and discussed.

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Linear LAV‐based state estimation integrating hybrid SCADA/PMU measurements

Cited by 31 publications

References 32 publications

Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Robust Hybrid Linear State Estimator Utilizing SCADA and PMU Measurements

Linear state estimation and bad data detection for power systems with RTU and PMU measurements

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