A hybrid state estimation scheme for power systems

Lin, Lao-Sheng; Linawati, Linawati; Jasa, Lie; Ambikairajah, Eliathamby

doi:10.1109/apccas.2002.1115064

Cited by 14 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For synchronous generator SE, [18] presented dynamic estimation technique using Kalman filtering for the second-order model where performance was investigated with respect to sampling rate and noise level. In [13], a hybrid observer scheme for estimation was used using third-order synchronous generator model and estimation of the third-order synchronous generator states was performed using square-root unscented Kalman filter (SQ-UKF) in [14]. In [11], a fourth-order synchronous generator model was used for the estimation using EKF and its variant.…”

Section: Introductionmentioning

confidence: 99%

“…Since then, a lot of adaptive filtering algorithms have been applied to the problem of DSE of power systems [9][10][11][12][13][14]. For synchronous generator SE, [18] presented dynamic estimation technique using Kalman filtering for the second-order model where performance was investigated with respect to sampling rate and noise level.…”

Section: Introductionmentioning

confidence: 99%

“…These synchronized devices take data samples at specific rates which aid in having an overview of the power system dynamics. Among the vast literature available on power system SE, many deal with the SE at the synchronous machine level [9][10][11][12][13][14][15][16]; however, this field is always open to better, accurate, robust and lesser computationally complex estimation techniques. To perform different analyses by the utility for large-scale power system, it is necessary to have a precise model of the power system (such as switch statuses, line parameters and their constraints) aided by precise representation of states.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

State Space Least Mean Fourth Algorithm for Dynamic State Estimation in Power Systems

Ahmed¹,

Moinuddin²,

Al‐Saggaf³

2015

Arab J Sci Eng

View full text Add to dashboard Cite

Power system dynamic state estimation (DSE) has always been a critical problem in studying power systems. One of the essential parts of power systems are synchronous machines. In this work, we dealt with the problem of DSE of a synchronous machine by introducing a novel state space-based least mean fourth (SSLMF) algorithm. The rationale behind the proposed algorithm is the fact that a power system may encounter non-Gaussian disturbances/state errors and the least mean fourth algorithm is proven to be better in such environments. Moreover, we have also introduced a normalized version of the proposed algorithm, namely state space normalized least mean fourth (SSNLMF) algorithm to deal with the stability issue under Gaussian disturbances. Another motivation for developing the SSLMF algorithm is its simplicity as compared to other model-based nonlinear filtering algorithms such as Kalman filter, extended Kalman filter (EKF). Moreover, we also investigate the performance of the recently introduced state space least mean square (SSLMS). Performance of the SSLMF and the SSLMS is compared with existing EKF in both Gaussian and non-Gaussian noise environments. Extensive simulation results are presented which show superiority B Muhammad Moinuddin of the proposed algorithms, and hence, it verifies our rationale behind the work.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

State Space Least Mean Fourth Algorithm for Dynamic State Estimation in Power Systems

Ahmed¹,

Moinuddin²,

Al‐Saggaf³

2015

Arab J Sci Eng

View full text Add to dashboard Cite

show abstract

“…Despite an abundant literature on the design of linear observers for hybrid systems, only few works are concerned with the design of nonlinear hybrid observers for hybrid systems (see for example (Lin et al, 2002)and (Pettersson, 2005)).…”

Section: Introductionmentioning

confidence: 99%

Exact Differentiation via Sliding Mode Observer for Switched Systems

Saadaoui

Djemaï

Manamanni

et al. 2006

IFAC Proceedings Volumes

View full text Add to dashboard Cite

“…The structure of the proposed hybrid observer is composed of a location observer and a continuous observer and applied for a non linear model of a driveline with discontinuous elasticity. Despite an abundant literature on the design of linear observers for hybrid systems, only few works concern the design of nonlinear hybrid observer for hybrid systems (see for example (Lin et al, 2002)).…”

Section: Introductionmentioning

confidence: 99%