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optimal estimation for Fault Section in Power System Based on Harmony Search Algorithm

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Optimal Estimation for Fault Section in Power System Based o...

第25届中国控制与决策会议

作者： Ping Ren Liqun Gao Nan Li School of Information Engineering Shenyang University School of Information Science and Engineering Northeastern University Shenyang University

ISBN: (纸本)9781467355339

In this paper, the nonlinear optimal control problem is formulated as a multi-objective mathematical optimization problem. Harmony search （HS） algorithm is one of the new heuristic algorithms. The HS optimization algorithm is introduced for the first time in solving the fault section estimation performance in power systems. A case on optimal estimation for fault section in the part of the 230KV Southern Brazilian electric power system is presented to show the methodology’s feasibility and efficiency, compared with the existing fault section estimation in power system methods, the search time of the HS optimization algorithm is shorter and the result is close to the ideal solution, simultaneously.

关键词： optimal estimation Fault section Power system Harmony search algorithm

An improved constraint method in optimal estimation of CO2 from GOSAT SWIR observations

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Science China Earth Sciences 2017年第2期60卷 286-296页

作者： ZOU MingMin CHEN LiangFu LI ShenShen FAN Meng TAO JinHua ZHANG Ying State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China

We propose an algorithm that combines a pre-processing step applied to the a priori state vector prior to retrievals, with the modified damped Newton method （MDNM）, to improve convergence. The initial constraint vector pre-processing step updates the initial state vector prior to the retrievals if the algorithm detects that the initial state vector is far from the true state vector in extreme cases where there are CO2 emissions. The MDNM uses the Levenberg-Marquardt parameter ~,, which ensures a positive Hessian matrix, and a scale factor a, which adjusts the step size to optimize the stability of the convergence. While the algorithm iteratively searches for an optimized solution using observed spectral radiances, MDNM adjusts parameters ）, and a to achieve stable convergence. We present simulated retrieval samples to evaluate the performance of our algorithm and comparing it to existing methods. The standard deviation of our retrievals adding random noise was less than 3.8 ppmv. After pre-processing the initial estimate when it was far from the true value, the CO2 retrieval errors in the boundary layers were within 1.2 ppmv. We tested the MDNM algorithm＇s performance using GOSAT Llb data with cloud screening. Our preliminary validations comparing the results to TCCON FTS measurements showed that the average bias was less than 1.8 ppm and the correlation coefficient was approximately 0.88, which was larger than for the GOSAT L2 product.

关键词： Retrieve optimal estimation CO2 GOSAT

Retrievals of aerosol optical depth and total column ozone from Ultraviolet Multifilter Rotating Shadowband Radiometer measurements based on an optimal estimation technique

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Frontiers of Earth Science 2014年第4期8卷 610-624页

作者： Chaoshun LIU Maosi CHEN Runhe SHI Wei GAO Key Laboratory of Geographic Information Science Ministry of Education East China Normal University Shanghai 200062 China USDA UV-B Monitoring and Research Program Natural Resource Ecology Laboratory Colorado State University Fort Collins CO 80523 USA

A Bayesian optimal estimation （OE） retrieval technique was used to retreive aerosol optical depth （AOD）, aerosol single scattering albedo （SSA）, and an asymmetry factor （g） at seven ultraviolet wavelengths, along with total column ozone （TOC）, from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer （UV-MFRSR） deployed at the Southern Great Plains （SGP） site during March through November in 2009. The OE technique specifies appropriate error covariance matrices and optimizes a forward model （Tropospheric ultraviolet radiative transfer model, TUV）, and thus provides a supplemental method for use across the network of the Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） for the retrieval of aerosol properties and TOC with reasonable accuracy in the UV spectral range under various atmo- spheric conditions. In order to assess the accuracy of the OE technique, we compared the AOD retreivals from this method with those from Beer＇s Law and the AErosol RObotic Network （AERONET） AOD product. We also examine the OE retrieved TOC in comparison with the TOC from the U.S. Department of Agriculture UV-B Monitoring and Research Program （USDA UVMRP） and the Ozone Monitoring Instrument （OMI） satellite data. The scatterplots of the estimated AOD from the OE method agree well with those derived from Beer＇s law and the collocated AERONET AOD product, showing high values of correlation coefficients, generally 0.98 and 0.99, and large slopes, ranging from 0.95 to 1.0, as well as small offsets, less than 0.02 especially at 368 nm. The comparison of TOC retrievals also indicates the promising accuracy of the OE method in that the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units （DU）. Validation of the OE retrievals on these selected dates suggested that the OE technique has its merits and can serve as a supplemental tool in further analyzing UVMRP data.

关键词： optimal estimation aerosol optical depth totalcolumn ozone Ultraviolet Multifilter Rotating ShadowbandRadiometer (UV-MFRSR) Aerosol Robotic Network(AERONET) Tropospheric ultraviolet radiative transfermodel (TUV)

Linear optimal estimation of Discrete-time Systems with Multiple Measurement Delays

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Linear Optimal Estimation of Discrete-time Systems with Mult...

第36届中国控制会议

作者： Shuai Liu Lihua Xie School of Control Science and Engineering Shandong University School of Electrical and Electronic Engineering Nanyang Technological University

ISBN: (纸本)9781538629185

In this paper, we consider an optimal estimation problem in the sense of least mean square error for linear discrete-time systems with multiple state delays in the measurement output. Since computation complexity is high for augmentation approach,a lot of researches have been dedicated to finding alternative ways for the optimal estimation design. In existing studies, two dimensional Riccati iteration is unavoidable for calculating the optimal gain. Meanwhile, in the continuous-time setting, the counterpart of the two dimensional Riccati equation is partial differential equation which is difficult to solve. We shall provide a new result that the gain of the optimal estimation is obtained in terms of the solution of a Retarded Riccati-like equation instead of two dimensional Riccati equation. Furthermore, by applying the result to single delay case, we have found a relationship between optimal estimation of systems with multiple delays and optimal prediction.

关键词： Riccati Equation Delay Systems optimal estimation

optimal estimation in Wireless Sensor Networks with Double Measurements and Multiplicative Noise

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Optimal Estimation in Wireless Sensor Networks with Double M...

第二十九届中国控制会议

作者： LU Xiao1,2,ZHANG Huanshui11.School of Control Science and Engineering,Shandong University,Jinan 250061,P.R.China2.College of Information and Electrical Engineering,Shandong University of Science and Technology,Qingdao 266510,P.R.China

The optimal estimation for wireless sensor network systems is studied,where the measurements are observed from two different wireless channels,and the system is corrupted by multiplicative *** the system model,the probability of each packet-drop of measurements is *** optimal estimator is derived by probability method and Kalman filtering formulae based on projection theorem,the proposed optimal estimator is different from previous works,and some properties of the estimation error covariance are proposed,which will be useful to analyze the statistical convergence properties and the upper and lower bounds on the expected state error covariance in future.

关键词： optimal estimation Double measurements Wireless sensor network Multiplicative noise

optimal fusion estimation for stochastic systems with cross-correlated sensor noises

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Science China(Information Sciences) 2017年第12期60卷 57-70页

作者： Liping YAN Yuanqing XIA Mengyin FU School of Automation Key Laboratory of Intelligent Control and Decision of Complex SystemsBeijing Institute of Technology

This paper is concerned with the optimal fusion of sensors with cross-correlated sensor *** taking linear transformations to the measurements and the related parameters, new measurement models are established, where the sensor noises are decoupled. The centralized fusion with raw data, the centralized fusion with transformed data, and a distributed fusion estimation algorithm are introduced, which are shown to be equivalent to each other in estimation precision, and therefore are globally optimal in the sense of linear minimum mean square error(LMMSE). It is shown that the centralized fusion with transformed data needs lower communication requirements compared to the centralized fusion using raw data directly, and the distributed fusion algorithm has the best flexibility and robustness and proper communication requirements and computation complexity among the three algorithms(less communication and computation complexity compared to the existed distributed Kalman filtering fusion algorithms). An example is shown to illustrate the effectiveness of the proposed algorithms.

关键词： optimal estimation distributed fusion Kalman filter cross-correlated noises linear transformation

optimal Linear State estimation for Discrete-time Systems with Time-correlated Multiplicative Noises and Delays

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Optimal Linear State Estimation for Discrete-time Systems wi...

第三十九届中国控制会议

作者： LiLi Kong Wei Wang School of Control Science and Engineering Shandong university

This brief is concerned with the filtering problem for discrete-time measurement-delay systems with time-correlated multiplicative noise. First, by using the reorganized innovation approach, the original system is transformed into a delay-free system. Then, several new recursive terms are added in the initial estimation of the new algorithm, including the estimation for the product of multiplicative measurement noise and state along with the corresponding error covariances. Based on the well-known projection theorem, a new algorithm for optimal filtering of the system under consideration is proposed.

关键词： discrete-time system measurement-delay time-correlated multiplicative noise optimal estimation

A gate size estimation algorithm for data association filters

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Science in China(Series F) 2008年第4期51卷 425-432页

作者： WANG MingHui WAN Qun YOU ZhiSheng College of Computer Science and Engineering Sichuan University Chengdu 610064 China College of Electronics Engineering University of Electronic Science and Technology Chengdu 610054 China

The problem of forming validation regions or gates for new sensor measurements obtained when tracking targets in clutter is considered. Since the gate size is an integral part of the data association filter, this paper is intended to describe a way of estimating the gate size via the performance of the data association filter. That is, the gate size can be estimated by looking for the optimal performance of the data association filter. Simulations show that this estimation method of the gate size offers advantages over the common and classical estimation methods of the gate size, especially in a heavy clutter and/or false alarm environment.

关键词： data association filter gate size optimal estimation

Singular value diagnosis in dam safety monitoring effect values

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Science China(Technological Sciences) 2011年第5期54卷 1169-1176页

作者： GU ChongShi ZHAO ErFeng JIN Yi SU HuaiZhi State Key Laboratory of Hydrology Water Resources and Hydraulic Engineering Hohai UniversityNanjing 210098China National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety Hohai UniversityNanjing 210098China College of Water Conservancy and Hydropower Engineering Hohai UniversityNanjing 210098China

Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.

关键词： dam safety monitoring effect singular value diagnosis principal component analysis optimal estimation