Optimal parameterization of Kalman filter based three-phase dynamic state estimator for active distribution networks

Monitoring and controlling the electrical distribution system for real time is becoming very important to improve its operating performance after transition to active distribution systems. So, many sensors are needed to monitor all parts in the systems. But if sensors are installed at all buses, investment cost becomes huge. To reduce the number of sensors, state estimation approach can be used to estimate the voltage of buses, which do not have sensors. State Estimation (SE) algorithms are broadly classified into Static State Estimator (SSE) and Dynamic State Estimator (DSE). This chapter classifies most algorithms used in active distribution networks, also State estimation in unbalanced distribution systems, and Role of PMU in Distribution System State Estimation.

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Online State Estimator for Three Phase Active Distribution Networks Displayed on Geographic Information System

Journal of Clean Energy Technologies ◽

10.7763/jocet.2014.v2.154 ◽

2014 ◽

Vol 2 (4) ◽

pp. 357-362

Author(s):

Dimas Fajar U. P. ◽

Indri Suryawati ◽

Ontoseno Penangsang ◽

Adi Suprijanto ◽

Mat Syai’in

Keyword(s):

Information System ◽

Geographic Information System ◽

Distribution Networks ◽

Geographic Information ◽

State Estimator ◽

Three Phase ◽

Active Distribution Networks

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An L-1 Regularized Forecasting-Aided State Estimator for Active Distribution Networks

IEEE Transactions on Smart Grid ◽

10.1109/tsg.2021.3115816 ◽

2021 ◽

pp. 1-1

Author(s):

Rajarshi Dutta ◽

Sreenath Jayakumar Geetha ◽

Saikat Chakrabarti ◽

Ankush Sharma

Keyword(s):

Distribution Networks ◽

State Estimator ◽

Active Distribution Networks

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Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm

Energies ◽

10.3390/en12234457 ◽

2019 ◽

Vol 12 (23) ◽

pp. 4457 ◽

Cited By ~ 1

Author(s):

Antončič ◽

Papič ◽

Blažič

Keyword(s):

Kalman Filter ◽

State Estimation ◽

Low Voltage ◽

Least Squares Method ◽

Weighted Least Squares ◽

Measurement Data ◽

Estimation Algorithm ◽

Distribution Networks ◽

Voltage Distribution ◽

State Estimator

This paper presents a novel approach for the state estimation of poorly-observable low voltage distribution networks, characterized by intermittent and erroneous measurements. The developed state estimation algorithm is based on the Extended Kalman filter, where we have modified the execution of the filtering process. Namely, we have fixed the Kalman gain and Jacobian matrices to constant matrices; their values change only after a larger disturbance in the network. This allows for a fast and robust estimation of the network state. The performance of the proposed state-estimation algorithm is validated by means of simulations of an actual low-voltage network with actual field measurement data. Two different cases are presented. The results of the developed state estimator are compared to a classical estimator based on the weighted least squares method. The comparison shows that the developed state estimator outperforms the classical one in terms of calculation speed and, in case of spurious measurements errors, also in terms of accuracy.

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