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Dynamic State Estimation for DFIG with Unknown Inputs Based on Cubature Kalman Filter and adaptive interpolation

Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1086-1099页

作者： Maolin Zhu Hao Liu Junbo Zhao Bendong Tan Tianshu Bi Samson Shenglong Yu State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijingChina Department of Electrical and Computer Engineering University of ConnecticutStorrs06269USA School of Engineering Deakin University75 Pigdons RoadWaurn PondsVIC3216Australia

Dynamic state estimation(DSE)accurately tracks the dynamics of power systems and demonstrates the evolution of the system state in real *** paper proposes a DSE approach for a doubly-fed induction generator(DFIG)with unknown inputs based on adaptive interpolation and cubature Kalman filter(AICKF-UI).DFIGs adopt different control strategies in normal and fault conditions;thus,the existing DSE approaches based on the conventional control model of DFIG are not applicable in all ***,the DSE model of DFIGs is reformulated to consider the converter controller outputs as unknown inputs,which are estimated together with the DFIG dynamic states by an exponential smoothing model and augmented-state cubature Kalman ***,as the reporting rate of existing synchro-phasor data is not sufficiently high to capture the fast dynamics of DFIGs,a large estimation error may occur or the DSE approach may *** this end,in this paper,a local-truncation-error-guided adaptive interpolation approach is *** simulations conducted on a wind farm and the modified IEEE 39-bus test system show that the proposed AICKF-UI can(1)effectively address the divergence issues of existing cubature Kalman filters while being computationally more efficient;(2)accurately track the dynamic states and unknown inputs of the DFIG;and(3)deal with various types of system operating conditions such as time-varying wind and different system faults.

关键词： adaptive interpolation cubature Kalman filter doubly-fed induction generator(DFIG) dynamic state estimation unknown input

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A NEW ALGORITHM OF THE NONLINEAR adaptive interpolation

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Journal of Electronics(China) 2006年第5期23卷 708-712页

作者： Shi Lingfeng Guo Baolong School of Electromechanical Engineering Xidian University Xi＇an 710071 China

The paper presents a new algorithm of NonLinearly adaptive interpolation (NLAI). NLAI is based on both the gradients and the curvature of the signals with the predicted subsection. It is characterized by adap- tive nonlinear interpolation method with extracting the characteristics of signals. Experimental research testi- fies the validity of the algorithm using the echoes of the Ground Penetrating Radar (GPR). A comparison of this algorithm with other traditional algorithms demonstrates that it is feasible.

关键词： Nonlinearity adaptive interpolation Ground Penetrating Radar (GPR)

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A novel adaptive image zooming scheme via weighted least-squares estimation

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Frontiers of Computer Science 2015年第5期9卷 703-712页

作者： Xuexia ZHONG Guorui FENG Jian WANG Wenfei WANG Wen SI Cyber Physical System Research and Development Center The Third Research Institute of Ministry of Public Security Shanghai 201204 China School of Communication and Information Engineering Shanghai University Shanghai 200444 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Chenrui Information Technology Company Shanghai 201204 China College of Information and Computer Science Shanghai Business School Shanghai 201400 China

A critical issue in image interpolation is preserving edge detail and texture information in images when zooming. In this paper, we propose a novel adaptive image zooming algorithm using weighted least-square estimation that can achieve arbitrary integer-ratio zoom （WLS-AIZ） For a given zooming ratio n, every pixel in a low-resolution （LR） image is associated with an n x n block of high-resolution （HR） pixels in the HR image. In WLS-AIZ, the LR image is interpolated using the bilinear method in advance. Model parameters of every n×n block are worked out through weighted least-square estimation. Subsequently, each pixel in the n × n block is substituted by a combination of its eight neighboring HR pixels using estimated parameters. Finally, a refinement strategy is adopted to obtain the ultimate HR pixel values. The proposed algorithm has significant adaptability to local image structure. Extensive experiments comparing WLS-AIZ with other state of the art image zooming methods demonstrate the superiority of WLS-AIZ. In terms of peak signal to noise ratio （PSNR）, structural similarity index （SSIM） and feature similarity index （FSIM）, WLS-AIZ produces better results than all other image integer-ratio zoom algorithms.

关键词： adaptive interpolation refinement strategy,weighted least-squares estimation arbitrary integer and WLS-AIZ scheme

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