Extended Kalman filter used to estimate speed rotation for sensorless MPPT of wind conversion chain based on a PMSG

2015 International Conference on Electrical and Information Technologies (ICEIT) Pub Date : 2015-03-25 DOI:10.1109/EITECH.2015.7162989

Amina Echchaachouai, Soumia El Hani, A. Hammouch, Said Guedira

{"title":"Extended Kalman filter used to estimate speed rotation for sensorless MPPT of wind conversion chain based on a PMSG","authors":"Amina Echchaachouai, Soumia El Hani, A. Hammouch, Said Guedira","doi":"10.1109/EITECH.2015.7162989","DOIUrl":null,"url":null,"abstract":"This paper presents an innovative method of determining the value of the optimum wind power employed to design a sensorless Maximum Power Point Tracking (MPPT) algorithm of a wind conversion chain with a Permanent Magnet Synchronous Generator (PMSG) using two estimators: the Extended Kalman Filter (EKF) to estimate rotation speed and the extremum seeking to estimate the coefficient including turbine parameters. The model of Wind Energy Conversion System (WECS) consists of a wind turbine, two-mass drive train, PMSG, and power converter supplying a DC load. The proposed method based on sensorless wind speed, air density and turbine parameters, generates the outputs to be used in the Field Oriented Control (FOC) requiring implementation of an active rectifier and also in the MPPT block. At first, we show the advantage of using a FOC of the PMSG. Then we describe the EKF and the extremum seeking method. Simulations on Matlab-Simulink can be found at the end of the paper, confirming the performance of the proposed approach.","PeriodicalId":405923,"journal":{"name":"2015 International Conference on Electrical and Information Technologies (ICEIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Electrical and Information Technologies (ICEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EITECH.2015.7162989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 6

Abstract

This paper presents an innovative method of determining the value of the optimum wind power employed to design a sensorless Maximum Power Point Tracking (MPPT) algorithm of a wind conversion chain with a Permanent Magnet Synchronous Generator (PMSG) using two estimators: the Extended Kalman Filter (EKF) to estimate rotation speed and the extremum seeking to estimate the coefficient including turbine parameters. The model of Wind Energy Conversion System (WECS) consists of a wind turbine, two-mass drive train, PMSG, and power converter supplying a DC load. The proposed method based on sensorless wind speed, air density and turbine parameters, generates the outputs to be used in the Field Oriented Control (FOC) requiring implementation of an active rectifier and also in the MPPT block. At first, we show the advantage of using a FOC of the PMSG. Then we describe the EKF and the extremum seeking method. Simulations on Matlab-Simulink can be found at the end of the paper, confirming the performance of the proposed approach.

查看原文本刊更多论文

将扩展卡尔曼滤波用于基于PMSG的无传感器风转换链MPPT转速估计

本文提出了一种确定最优风力值的创新方法，并设计了一种永磁同步发电机(PMSG)风力转换链无传感器最大功率点跟踪(MPPT)算法，该算法使用扩展卡尔曼滤波(EKF)估计转速，极值求法估计包含涡轮机参数的系数。风能转换系统(WECS)模型由风力发电机、双质量传动系统、PMSG和提供直流负载的电源变换器组成。所提出的方法基于无传感器风速、空气密度和涡轮参数，产生用于需要实现有源整流器的场定向控制(FOC)和MPPT块的输出。首先，我们展示了使用PMSG的FOC的优点。然后描述了EKF和极值求法。论文最后在Matlab-Simulink上进行了仿真，验证了所提方法的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2015 International Conference on Electrical and Information Technologies (ICEIT)

自引率

0.00%

发文量