{"title":"Experimental Validation of Direct Predictive Control of Variable Speed Wind Energy Conversion System Based on DFIG","authors":"S. Chikha, K. Barra, A. Reama","doi":"10.3311/ppee.18874","DOIUrl":null,"url":null,"abstract":"The paper presents the design and the implementation of a direct predictive control of a variable speed wind energy conversion system. The conversion chain uses a Doubly Fed Induction Generator DFIG whereas the control method is based on a Finite States Model Predictive Control FS-MPC. The proposed control method selects the optimal switching state of the two levels back to back power converter that minimizes the cost function, where this optimal voltage vector is applied on the output of the power converter in next sampling time. The proposed predictive control strategy uses only one sample time prediction and it is intuitive since it is very simple for implementation. In order to adjust the measured rotor currents to track their references, the error between orthogonal rotor current components predictions to their computed values used to select the optimal vector and applied on the power converter in rotor side CSR in next sampling time. On other side, based on the error between the active and reactive power prediction and their references of the electrical grid, the predictive algorithm control of the gird side converter CSG kept the Dc-link voltage constant and guarantee that the whole system functioning with unity power factor. The experimental results confirm the advantages of using this structure for wind energy conversion system and the effectiveness of the proposed control strategy.","PeriodicalId":37664,"journal":{"name":"Periodica polytechnica Electrical engineering and computer science","volume":"6 1","pages":"174-190"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Periodica polytechnica Electrical engineering and computer science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3311/ppee.18874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
The paper presents the design and the implementation of a direct predictive control of a variable speed wind energy conversion system. The conversion chain uses a Doubly Fed Induction Generator DFIG whereas the control method is based on a Finite States Model Predictive Control FS-MPC. The proposed control method selects the optimal switching state of the two levels back to back power converter that minimizes the cost function, where this optimal voltage vector is applied on the output of the power converter in next sampling time. The proposed predictive control strategy uses only one sample time prediction and it is intuitive since it is very simple for implementation. In order to adjust the measured rotor currents to track their references, the error between orthogonal rotor current components predictions to their computed values used to select the optimal vector and applied on the power converter in rotor side CSR in next sampling time. On other side, based on the error between the active and reactive power prediction and their references of the electrical grid, the predictive algorithm control of the gird side converter CSG kept the Dc-link voltage constant and guarantee that the whole system functioning with unity power factor. The experimental results confirm the advantages of using this structure for wind energy conversion system and the effectiveness of the proposed control strategy.
期刊介绍:
The main scope of the journal is to publish original research articles in the wide field of electrical engineering and informatics fitting into one of the following five Sections of the Journal: (i) Communication systems, networks and technology, (ii) Computer science and information theory, (iii) Control, signal processing and signal analysis, medical applications, (iv) Components, Microelectronics and Material Sciences, (v) Power engineering and mechatronics, (vi) Mobile Software, Internet of Things and Wearable Devices, (vii) Solid-state lighting and (viii) Vehicular Technology (land, airborne, and maritime mobile services; automotive, radar systems; antennas and radio wave propagation).