PMU Data Buffering for Power System State Estimators

Murugesan, Veerakumar; Chakhchoukh, Yacine; Vittal, Vijay; Heydt, G.T.; Logic, Naim; Sturgill, Steve

doi:10.1109/jpets.2015.2448115

Cited by 28 publications

(15 citation statements)

References 21 publications

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“…In future, we will proof the convergence using theoretical analysis over packet loss. Moreover, we will develop a dynamic state estimation algorithm with buffer when communication fails , .…”

Section: Discussionmentioning

confidence: 99%

Estimating and Controlling the Renewable Microgrid States Using IoT Infrastructure

Rana

Chen

2019

Asian Journal of Control

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This paper considers the optimal filter design issue for microgrid state estimation and stabilisation under packet loss conditions. The considered internet of things (IoT) technologies collect system state information from sensors and send control messages to actuators where they are connected over a lossy communication network. From signal processing point of view, this paper develops an optimal state estimation algorithm using the mean squared error principle. Then a feedback controller is designed under the condition of packet dropouts in the communication network. Finally, the convergence of the developed algorithm is numerically shown. The performance of the proposed schemes are demonstrated using the renewable microgrid. KEYWORDSController under lossy channel, dynamic state estimation, internet of things, microgrid, packet dropouts the IoT devices are used for accommodating home appliances information, and communicating between green homes and networked control system in cloud server via the internet. These type of Kalman filter algorithms are extensively applied in different applications such as

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Section: Discussionmentioning

confidence: 99%

Estimating and Controlling the Renewable Microgrid States Using IoT Infrastructure

Rana

Chen

2019

Asian Journal of Control

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“…In [70], the problem that how buffering the phasor measurements can improve the state estimate has been investigated. Furthermore, the optimal buffer design and the use of the phasor measurements from that buffer have been addressed in [71].…”

Section: A Methodologiesmentioning

confidence: 99%

Recent advances on state estimation for power grids with unconventional measurements

Wang

Liu

et al. 2017

IET Control Theory & Applications

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State estimation problem for power systems has long been a fundamental issue that demands a variety of methodologies dependent on the system settings. With recent introduction of advanced devices of phasor measurement units (PMUs) and dedicated communication networks, the infrastructure of power grids has been greatly improved. Coupled with the infrastructure improvements are three emerging issues for the state estimation problems, namely, the coexistence of both traditional and PMU measurements, the incomplete information resulting from delayed, asynchronous and missing measurements due to communication constraints, and the cyber-attacks on the communication channels. In this paper, we aim to survey some recent advances on the state estimation methods which tackle the above three issues in power grids. Traditional state estimation methods applied in power grids are first introduced. Latest results on state estimation with mixed measurements and incomplete measurements are then discussed in great detail. In addition, the techniques developed to ensure the cyber-security of the state estimation schemes for power grids are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out.

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“…It should be noted that sampling rates of SCADA and PMU measurements are not the same. This problem also known as the time skew problem can be dealt with by buffering PMU measurements [33], [34].…”

Section: Exact Linear Formulations For Measurementsmentioning

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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PMU Data Buffering for Power System State Estimators

Cited by 28 publications

References 21 publications

Estimating and Controlling the Renewable Microgrid States Using IoT Infrastructure

Estimating and Controlling the Renewable Microgrid States Using IoT Infrastructure

Recent advances on state estimation for power grids with unconventional measurements

Robust Hybrid Linear State Estimator Utilizing SCADA and PMU Measurements

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