A new adaptive neuro-fuzzy inference system (ANFIS) and PI controller to voltage regulation of power system equipped by wind turbine

被引：0
|
作者：
Griche I. [1 ,2 ]
Messalti S. [1 ]
Saoudi K. [2 ]
Touafek M.Y. [2 ]
机构：
[1] Department of Electrical Engineering, Faculty of technology, University of M’sila, M’sila
[2] Department of Electrical Engineering, Faculty of Engineering, University of Bouira, Bouira
来源：
European Journal of Electrical Engineering | 2019年 / 21卷 / 02期
关键词：
Distributed generator (DG); Intelligent controller; Power network; Simulation;
D O I：
10.18280/ejee.210204
中图分类号：
学科分类号：
摘要：
In this paper, new Adaptive Neuro-Fuzzy Inference System (ANFIS) and PI controller have been proposed and investigated which the power system is equipped by Static Var Compensator (SVC) and small wind turbine. The SVC is controlled by PI controller optimized by genetic algorithm (GA) to regulate the voltage profile. To demonstrate the efficiency of proposed controller, a Single Machine Infinite Bus (SMIB) has been considered, in which small fluctuation of mechanical damped has been applied to improve the transient stability and has been evaluated using a relative rotor criteria. Obtained results have demonstrated a better performance with ANFIS and PI controller in which both voltage and transient stability have been controlled perfectly. © 2019 International Information and Engineering Technology Association. All rights reserved.
引用
收藏
页码：149 / 155
页数：6
相关论文
共 50 条
  • [21] Missing wind data forecasting with adaptive neuro-fuzzy inference system
    Fatih O. Hocaoglu
    Yusuf Oysal
    Mehmet Kurban
    Neural Computing and Applications, 2009, 18 : 207 - 212
  • [22] Fuzzy membership function design: An adaptive neuro-fuzzy inference system (ANFIS) based approach
    Kabir, Monika
    Kabir, Mir Md Jahangir
    2021 INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND INFORMATICS (ICCCI), 2021,
  • [23] Multioutput Adaptive Neuro-fuzzy Inference System
    Benmiloud, T.
    RECENT ADVANCES IN NEURAL NETWORKS, FUZZY SYSTEMS & EVOLUTIONARY COMPUTING, 2010, : 94 - 98
  • [24] Improved adaptive neuro-fuzzy inference system
    Tarek Benmiloud
    Neural Computing and Applications, 2012, 21 : 575 - 582
  • [25] Parallel Fuzzy Logic and PI Controller for Transient Stability and Voltage Regulation of Power System Including Wind Turbine
    Griche, Issam
    Messalti, Sabir
    Saoudi, Kamel
    PRZEGLAD ELEKTROTECHNICZNY, 2019, 95 (09): : 51 - 56
  • [26] Improved adaptive neuro-fuzzy inference system
    Benmiloud, Tarek
    NEURAL COMPUTING & APPLICATIONS, 2012, 21 (03): : 575 - 582
  • [27] Fuzzy controller for rapid nickel-cadmium batteries charger through adaptive neuro-fuzzy inference system (ANFIS) architecture
    Khosla, A
    Kumar, S
    Aggarwal, KK
    NAFIPS'2003: 22ND INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS PROCEEDINGS, 2003, : 540 - 544
  • [28] An adaptive neuro-fuzzy inference system (ANFIS) model for high pressure die casting
    Tsoukalas, V. D.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, 2011, 225 (B12) : 2276 - 2286
  • [29] ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) FOR FORECASTING: THE CASE OF THE CZECH STOCK MARKET
    Jankova, Zuzana
    15TH ANNUAL INTERNATIONAL BATA CONFERENCE FOR PH.D. STUDENTS AND YOUNG RESEARCHERS (DOKBAT), 2019, : 457 - 465
  • [30] Optimization of Photosynthetic Rate Parameters using Adaptive Neuro-Fuzzy Inference System (ANFIS)
    Valenzuela, Ira C.
    Baldovino, Renann G.
    Bandala, Argel A.
    Dadios, Elmer P.
    2017 INTERNATIONAL CONFERENCE ON COMPUTER AND APPLICATIONS (ICCA), 2017, : 129 - 134
12345