Measurement Sensitivity and Estimation Error in Distribution System State Estimation using Augmented Complex Kalman Filter

Louis, Alan; Ledwich, Gerard; Walker, Geoffrey R.; Mishra, Yateendra

doi:10.35833/mpce.2019.000160

Cited by 13 publications

(13 citation statements)

References 27 publications

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“…Kalman filter (KF)-based strategies are commonly used in FASE methods [5]- [7]. The KF is a recursive estimator, which considers the dynamic approach of the system, compared with the WLS as a snapshot estimator [8], [9]. When the system is nonlinear and can be well approximated by linearization, the extended Kalman filter (EKF) is a good choice for the SE [3].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, estimating the real and imaginary parts of the states independently is not sufficient due to the existing interactions between the real and imaginary parts. Therefore, the complex-valued states and the complex statistics are proposed in [8] and [12]. The augmented complex Kalman filter (ACKF) based on the direct approach is a noniterative DSSE technique that is used to overcome complex-valued nonlinear signals with strong levels of correlations.…”

Section: Introductionmentioning

confidence: 99%

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Distribution System State Estimation Using PV Separation Strategy in LV Feeders With High Levels of Unmonitored PV Generation

Mokaribolhassan

Nourbakhsh

Ledwich

et al. 2023

IEEE Systems Journal

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Distribution system state estimation (DSSE) is a critical analysis tool for active distribution networks (DNs). Unlike weighted least squares techniques, which are static DSSE methods, the augmented complex Kalman filter (ACKF) is a novel technique that considers the system's dynamic behavior. Currently, most DNs integrate a large number of unmonitored residential photovoltaic (PV) generations. Existing unmeasured PV sources violate the white noise assumption in Kalman and least-squaresbased estimators, causing the estimator to be biased. Because the one-step difference of aggregated customer demand is characterized as white noise, the suggested PV estimation technique based on the differencing strategy is used to decouple PV from the measured load. Using the specified contribution factors, the new online pseudo current injections are generated. In addition, the estimator's accuracy is improved by using a new PV-scalingaided ACKF approach based on the PV separation strategy. For validation purposes, this method is applied to real DN case studies. This study also makes use of an actual dataset to illustrate the efficacy of the proposed technique. The proposed technique outperforms the existing snapshot and dynamic DSSE techniques, and significant improvements are achieved in terms of accuracy and computational cost.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distribution System State Estimation Using PV Separation Strategy in LV Feeders With High Levels of Unmonitored PV Generation

Mokaribolhassan

Nourbakhsh

Ledwich

et al. 2023

IEEE Systems Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…In particular, a filter is commonly used to improve the aforementioned issues. All types of developed filters to achieve the parameter estimation and the effective control are presented, including Kalman filter [40], linear filter [41], transversal recursive filter [42], particle filter [43], adaptive filter [44], and dissipative filter [45], etc. Shen and Ding [46] discussed a hierarchical multi-innovation gradient scheme for a Hammerstein system by using a linear filter.…”

Section: Introductionmentioning

confidence: 99%

“…(2) A filter gain is proposed to obtain useful identification data from the collected system data, in which the strict restrictions are not required compared with published filters [40], [41], [44].…”

Section: Introductionmentioning

confidence: 99%

A New Robust Identification Algorithm for Hammerstein-Like System Using Identification Error Structure

Wang

2022

IEEE Access

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A new robust identification algorithm is introduced in this study for a Hammersteinlike system based on identification error information. With the help of the half-substitution idea, the identification model is converted into a compact model where the coupling parameters are avoided. To reduce the effect of noise signals, a filter gain is proposed to obtain helpful system data. Then, on the basis of the filtered variables and developed forcing variables, the identification error information is extracted from the helpful system data. By using the identification error data, a new parameter estimation adaptive law that differs from the classic prediction error method is derived. Therefore, a new identification scheme framework is proposed and the weakness of the prediction error method is improved. Simulations and a real-life plant are presented to test the validity and practicality of the presented identification approach.The results of parameter estimation and estimation error qualitatively demonstrated the advantages of the proposed algorithm. The computational complexity and performance evaluation indicators results quantitatively indicated that the proposed algorithm produces higher estimation performance compared with the other algorithms.

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“…This paper contributes an online estimation technique to measure voltage and current states under high DG penetration [8]. Reference [9] utilizes error covariance in distribution system state estimation to provide a technique for obtaining optimal measurement locations. A gradient-based multi-area algorithm is proposed for the distribution network state estimation, and it is expressed through a weighted least squares problem in [10].…”

Section: Introductionmentioning

confidence: 99%

Voltage Estimation of Active Distribution Network Using PMU Technology

Tangi

Gaonkar

2021

IEEE Access

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As the Distributed Generation (DG) is evolving, the distribution network has undergone tremendous change. The DG sources like wind and solar are intermittent in nature. Hence to estimate the Active distribution network's (ADN) parameters (Voltage and Current) accurately with the DG variation, the traditional offline method like long-term smart distribution network planning (with off-line variant) method is not feasible in terms of network's reliability and operation. In this work, an online voltage estimation technique using PMU (Phasor Measurement Unit) technology is proposed to enhance a distribution network's reliable operation and real-time monitoring. The proposed estimation method does not require PMU units at all nodes in the network. The estimation of unknown states information can be achieved from available PMU unit's data. The proposed methodology is economical and feasible for voltage estimation, and system observability as the number of PMU units required is less. The standard IEEE Distribution network systems are considered for checking the feasibility of the recommended technique. For the simulation of the case studies, MATLAB programming is used. A Forward and Backward sweep (FBS) load-flow algorithm is used to authenticate the proposed methodology.

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Measurement Sensitivity and Estimation Error in Distribution System State Estimation using Augmented Complex Kalman Filter

Cited by 13 publications

References 27 publications

Distribution System State Estimation Using PV Separation Strategy in LV Feeders With High Levels of Unmonitored PV Generation

Distribution System State Estimation Using PV Separation Strategy in LV Feeders With High Levels of Unmonitored PV Generation

A New Robust Identification Algorithm for Hammerstein-Like System Using Identification Error Structure

Voltage Estimation of Active Distribution Network Using PMU Technology

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