Frequency Estimation of Distorted Power System Signals Using Robust Extended Complex Kalman Filter

Huang, Chien-Hung; Lee, Chien-Hsing; Shih, Kuang-Jung; Wang, Yaw-Juen

doi:10.1109/isap.2007.4441663

Cited by 6 publications

(4 citation statements)

References 22 publications

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“…State-space models have been designed for estimating the fundamental frequency iteratively. The state-space is build from a single phase voltage in [15], three phase voltages are taken into account in [7]. However, all these models only deal with either a single phase of a power system (as the ones in [27], [15]) or a balanced three phase power system (as in [7]).…”

Section: Fundamental Frequency Estimationmentioning

confidence: 99%

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A dedicated state space for power system modeling and frequency and unbalance estimation

2017

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Over the last decades, a great deal of research has been focused on power quality issues in electrical energy transportation. We present a statespace representation to model dynamical power systems like electrical distribution systems. The proposed model is able to take into account all the dynamic behavior of a multiphase power system. It has been applied to model a typical three-phase power system and its unbalance, i.e., an electrical grid which can be perturbed by nonlinear loads and distributed renewable energy generation which is a typical changing system. Associated with an extended Kalman filter, the state-space model is used to iteratively estimate power quality parameters. Indeed, the symmetrical components of the power system, i.e., their amplitude and phase angle values, and the fundamental frequency can be calculated at each iteration without any prior knowledge. The proposed estimation technique is an evolving and adaptive method able to handle the changing power system. Its effectiveness has been evaluated by several tests. Results have been compared to other methods. They show the efficiency and better performance of the proposed method. The fundamental frequency and the symmetrical components are precisely estimated even under disturbed and time-varying conditions. This state-space representation can therefore be used in active power filtering schemes and in load frequency control strategies.

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Section: Fundamental Frequency Estimationmentioning

confidence: 99%

“…Mathematically, power quality can be defined with a set of several parameters and indicators, obviously, some of them have a physical interpretation [9]. Estimating and monitoring these parameters in real-time allows to prevent against troubles and failures [15] ; actions can thus be operated in an appropriate way [22], [32].…”

Section: Introductionmentioning

confidence: 99%

A dedicated state space for power system modeling and frequency and unbalance estimation

2017

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“…Fast and precise harmonics compensation [4] and fault detection [5] necessitate an online estimation and tracking of the fundamental frequency in power lines. For example, power quality can be ensured by Active Power Filter (APF) devices.…”

Section: Introductionmentioning

confidence: 99%

“…State-space models have been designed for estimating the fundamental frequency iteratively. The state-space is build from a single phase voltage in [5], three phase voltages are taken into account in [8]. However, all these models only deal with either a single phase of a power system (as the ones in [7], [5]) or a balanced three phase power system (as in [8]).…”

Section: Introductionmentioning

confidence: 99%

A new state-space for unbalanced three-phase systems: Application to fundamental frequency tracking with Kalman filtering

Phan

Hermann

Wira

2016

2016 18th Mediterranean Electrotechnical Conference (MELECON)

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In nowadays electrical grids with distributed renewable energy generation, in microgrids and smart grids, the estimation of the fundamental frequency in a fast and precise way is essential. This paper introduces a new state-space model to be used with an Extended Kalman Filter (EKF) for estimating the frequency of power system signals in real-time. The proposed model takes into account all the characteristics of a general threephase power system and mainly the unbalance. Therefore, the symmetrical components of the power system, i.e., their amplitude and phase angle values, can also be deduced at each iteration from the proposed state-space model. The effectiveness of the method has been evaluated. Results and comparisons of online frequency estimation and symmetrical components identification show the efficiency of the proposed method. The frequency is precisely estimated from time-varying signals disturbed by higher-order harmonics.

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A new state-space model for three-phase systems for Kalman filtering with application to power quality estimation

Phan

Hermann

et al. 2015

AIP Conference Proceedings

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Frequency Estimation of Distorted Power System Signals Using Robust Extended Complex Kalman Filter

Cited by 6 publications

References 22 publications

A dedicated state space for power system modeling and frequency and unbalance estimation

A dedicated state space for power system modeling and frequency and unbalance estimation

A new state-space for unbalanced three-phase systems: Application to fundamental frequency tracking with Kalman filtering

A new state-space model for three-phase systems for Kalman filtering with application to power quality estimation

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