최적 FIR 평활기를 이용한 전력 시스템 고조파 성분 추정 기법 (Power System Harmonic Estimation using Optimal Finite Impulse Response Smoother)

서지정보

· 발행기관 : 제어·로봇·시스템학회
· 수록지 정보 : 제어.로봇.시스템학회 논문지 / 24권 / 12호 / 1095 ~ 1100페이지
· 저자명 : 권보규

초록

In this paper, an optimal finite impulse response (FIR) smoother based power system harmonics estimation method is proposed. The current or voltage signal with measurement noise is represented by a state-space model and then a time-invariant optimal FIR smoother is applied to the state-space model in order to estimating the harmonic components. Since the optimal FIR smoother has bounded-input bounded-output (BIBO) stability, the proposed method could prevent the divergence problem that may occur in Kalman estimator based approaches. In addition, the proposed method could provide more accurate estimation results and faster convergence properties than the optimal filter-based method because the smoother uses more information than the filter. Moreover, the proposed method gives a more general solution than the optimal FIR filter based harmonic estimation method since the optimal FIR smoother is reduced to the optimal FIR filter when the fixed lag size of the smoother is zero. Through numerical examples, the performance of the proposed method is verified by comparing with a time-varying Kalman filter based method and an optimal FIR filter-based method.

영어초록

In this paper, an optimal finite impulse response (FIR) smoother based power system harmonics estimation method is proposed. The current or voltage signal with measurement noise is represented by a state-space model and then a time-invariant optimal FIR smoother is applied to the state-space model in order to estimating the harmonic components. Since the optimal FIR smoother has bounded-input bounded-output (BIBO) stability, the proposed method could prevent the divergence problem that may occur in Kalman estimator based approaches. In addition, the proposed method could provide more accurate estimation results and faster convergence properties than the optimal filter-based method because the smoother uses more information than the filter. Moreover, the proposed method gives a more general solution than the optimal FIR filter based harmonic estimation method since the optimal FIR smoother is reduced to the optimal FIR filter when the fixed lag size of the smoother is zero. Through numerical examples, the performance of the proposed method is verified by comparing with a time-varying Kalman filter based method and an optimal FIR filter-based method.

참고자료

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