NDLI: Forecast aided measurements data synchronisation in robust power system state estimation

Content Provider	IET Digital Library
Author	Khosravi, Mohsen Banejad, Mahdi Shandiz, Heydar Toossian
Abstract	Backbone of a real time monitoring and controlling operations in power systems is state estimation. The main goal of the paper is to use all useful data (collected by measurements) in the process of the robust state estimation. Data acquisition by Phasor Measurement Units (PMUs) has an important role in providing an accurate robust forecasted estimator. Conventional measurements have much lower data transfer rate than the PMUs. On other hands, the number of received data from PMUs is fewer than the conventional measurements and due to this fact, the state of the system are not observable by only PMUs. This fact leads to use the benefits of all kind of measured data. Robustness of the proposed method is guaranteed by rejecting outlier (large amplitude error) by forecasting conventional measurements data and using robustness property of the Kalman filter against noise in data (small amplitude error). Moreover, the proposed estimator tracks dynamic behavior of system much faster than traditional methods. The proposed estimator has been implemented on the IEEE 9-bus and the IEEE 118-bus systems. Comparison results of the proposed algorithm with those of a traditional dynamic estimator proves the efficiency, accuracy and robustness of the proposed method against falsified data.
Starting Page	2379
Ending Page	2388
Page Count	10
ISSN	17518687
Volume Number	10
e-ISSN	17518695
Issue Number	Issue 10, Jul (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/10/10
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2015.1138
Journal	IET Generation, Transmission & Distribution
Publisher Date	2016-07-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Control of Electric Power System Data Acquisition Data Acquisition System Data Falsification Decision Making Digital Signal Processing Dynamic Estimator Extended Kalman Filter Filtering Method in Signal Processing Forecast Aided Measurement Data Synchronisation IEEE 118-bus System IEEE 9-bus System Kalman Filter Learned Neural Network Neural Computing Technique Neural Nets Phasor Measurement Phasor Measurement Unit PMU Power Engineering Computing Power System Control Power System Controlling Operation Power System Measurement And Metering Power System State Estimation Pseudodynamic Equation Real-time Monitoring Robust Power System State Estimation Robustness Property Sampling Time State Vector Synchronisation Synchronised Data
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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