Wyniki 1-3 spośród 3 dla zapytania: authorDesc:"Yong LI"

Denoising and detrending of measured oscillatory signal in power system

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This paper presents a novel method for denoising and detrending of oscillatory signal measured from wide area measurement system (WAMS) using empirical mode decomposition (EMD) and time-frequency analysis. First of all, the measured signal is decomposed into a set of intrinsic mode functions (IMFs) by EMD. Next, the IMFs are divided into three parts based on their time and frequency distributions. Then, the noise and higher frequency components, trend components and meaningful oscillation modes are identified respectively. The proposed method are validated by the actual measured signal from WAProtector and the estimated trend is confirmed by comparing with the sliding linear trend estimated method and other nonlinear trend estimated methods. Streszczenie. W artykule zaprezentowano nową metodę usuwania szumu z sygnału okresowego w systemach WAMS. W pierwszej kolejności przeprowadza się dekompozycję sygnału na funkcje, które następnie dzielone są na trzy części w zależności od rozkładu czasowoczęstotliwościowego. (Usuwanie szumu i trendu w zmierzonym sygnale okresowym systemu WAMS) Keywords: empirical mode decomposition; intrinsic mode functions; signal energy; frequency distribution estimated trend Słowa kluczowe: szum, trend, WAMS. Introduction In recent years, Wide Area Measurement System (WAMS) based Phasor Measurement Units (PMUs) has been built, which provides favorable opportunity to monitor and analyze dynamic features of inter-connected power system near on real time [1,2]. Nevertheless, the information, which contains useful data and captured by WAMS, are polluted by kinds of noise. It requires outstanding techniques to extract and estimate the oscillation modes and parameters of interests. Denoising and detrending of oscillatory signal is important for several reasons. First, the meaningful oscillation modes are polluted by all kinds of noise. Therefore, denoising is the first step before application of modal identificatio[...]

Mid-long-Term Regional Load Forecasting based on Census X12-SARIMA Model

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Regional power load time series has obviously trend circulation and seasonal cycle etc characteristics. In addition, using Census X12, such time series can be decomposed into trend circulation element, season element, irregular element etc. The paper attempts to establish a Census X12-SARIMA season adjustment model for mid-long-term regional power load analysis and prediction.Through empirical test for 92 months power load of Guangzhou and Suzhou area, 12 monthly power load from 2011.9 to 2012.8 was predicted. The results proved that Census X12- SARIMA model is effective in mid-long-term regional power load analysis and prediction. Streszczenie. W artykule podjęto próbę dopasowania modelu energetycznego Census X12-SARIMA na potrzeby średnio-okresowych analiz i predykcji obciążenia energetycznego. Na podstawie testów empirycznych, opartych na danych z 92 miesięcy obciążenia energetycznego regionów Guangshou i Suzhou, stworzony został 12 miesięczny profil- 09.2011-08.2012. Wyniki dowodzą ze Census X12-SARIMA jest efektywny w analizie średnio-okresowej (Przewidywanie obciążenia średnio-okresowego, na podstawie modelu Census X12_SARIMA). Keywords: seasonal adjustment;Census X12-SARIMA model;load forecasting Słowa kluczowe: dopasowanie sezonowe, model Census X12-SARIMA, przewidywanie obciążenia. 1 Introduction Statistics shows that as a time series, regional power load often present obvious tendency, cyclical, seasonal and other non-stationary characteristics [1]. Research literature suggests that SARIMA [2,3] model has unique advantage in the analysis of such obviously season periodic series. In addition, using Census X12 [4], such time series can be decomposed into trend circulation element, season element, irregular element etc and researched. Therefore, based on the SARIMA model and Census X12 season adjustment method, this paper attempts to establish a Census X12-SARIMA season adjustment model for midlong- term regional[...]

Wide-area measurement-based time-delay damping control of SSSC-type FACTS device for stability enhancement of power system

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This paper presents a linear matrix inequality (LMI) method for the design of the wide-area time-delay damping (WATDD) controller of static synchronous series compensator (SSSC)-type flexible ac transmission system (FACTS) device to enhance the power stability of the interconnected power systems. Firstly, in order to reveal the single-input multi-output (SIMO) characteristic of the open-loop power system with SSSC-type FACTS device, the prediction error estimation (PEE) algorithm based system identification method is applied to fit a special SIMO linear model. Then, based on the robust control theory and LMI method, the identified linear model is formulated as the standard control problem with the time-delay of the input signals of the WATDD controller, and combined with the designed state observer for the input state variables of the WATDD controller, the control parameters are optimized by the LMI iterative solution algorithm. Finally, the nonlinear simulation on the typical 2-area 4- machine system installed with SSSC-type WATDD controller is performed to verify the LMI-based design method and the proposed SSSC-type WATDD controller. Streszczenie. W artykule przedstawiono metodę nierówności matrycy liniowej (LMI) do projektowania kontrolera z opóźnieniem kompensatora szeregowego synchronicznego (SSSC) elastycznego systemu przesyłowego prądu przemiennego (FACTS) w celu zwiększenia stabilności wzajemnie połączonych systemów zasilania. Po pierwsze, dopasowano specjalny model liniowy SIMO do charakterystyki otwartego systemu z urządzeniem SSSC-FACTS. Następnie, w oparciu o odporną teorię sterowania i metodę LMI, opisano zidentyfikowany model jako standardowy problem sterowania z opóźnieniem czasowym sygnałów wejściowych kontrolera WATDD i połączono go z utworzonym obserwatorem stanu wielkości wejściowych kontrolera WATDD - parametry sterowania są optymalizowane iteracyjnie za pomocą algorytmu LMI. W końcu, przeprowadzono symulację nieliniową [...]

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