Adaptive Three-phase Estimation of Sequence Components and Frequency Using H∞ Filter Based on Sparse Model

作     者：Umamani Subudhi Harish Kumar Sahoo Sanjeev Kumar Mishra Umamani Subudhi;Harish Kumar Sahoo;Sanjeev Kumar Mishra

作者机构：Department of Electronics and Telecommunication EngineeringIndian Institute of Information Technology(IIIT)BhubaneshwarIndia Department of Electronics and Telecommunication EngineeringVeer Surendra Sai University of Tecnology(Burla)SambalpurIndia 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2020年第8卷第5期

页      面：981-990页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0808[工学-电气工程] 080802[工学-电力系统及其自动化] 0809[工学-电子科学与技术（可授工学、理学学位）] 080902[工学-电路与系统] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：the support of Indian Institute of Information Technology,Bhubaneswar,India Veer Surendra Sai University of Tecnology(Burla),Sambalpur,India,in terms of Laboratory and online Journal facilities to carry out this research work 

主　　题：Sequence component Clarke transformation H∞filter state space model 

摘      要：The estimation of sequence or symmetrical components and frequency in three-phase unbalanced power system is of great importance for protection and relay.This paper proposes a new H∞filter based on sparse model to track the sequence components and the frequency of three-phase unbalanced power systems.The inclusion of sparsity improves the error convergence behavior of estimation model and hence short-duration non-stationary PQ events can easily be tracked in the time domain.The proposed model is developed using l1 norm penalty in the cost function of H∞filter,which is quite suitable for estimation across all the three phases of an unbalanced system.This model uses real state space modeling across three phases to estimate amplitude and phase parameters of sequence components.However,frequency estimation uses complex state space modeling and Clarke transformation generates a complex measurement signal from the unbalanced three-phase voltages.The state vector used for frequency estimation consists of two state variables.The proposed sparse model is tested using distorted three-phase signals from IEEE-1159-PQE database and the data generated from experimental laboratory setup.The analysis of absolute and mean square error is presented to validate the performance of the proposed model.