Intelligent controlled-wind-turbine emulator and induction-generator system using RBFN

Lin, Faa-Jeng; Teng, Li-Tao; Shieh, Po-Huang; Li, Y.-F.

doi:10.1049/ip-epa:20050540

Cited by 38 publications

(35 citation statements)

References 21 publications

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“…[25], [26], [27], [28], [29], [30], [31], [32], [33] Wind power - [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52], [53], [54], [55], [56], [57] [24]…”

Section: Resultsmentioning

confidence: 99%

Renewable energy emulation concepts for microgrids

Prieto‐Araujo

Olivella‐Rosell

Cheah-Mañé

et al. 2015

Renewable and Sustainable Energy Reviews

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This article reviews the renewable energy systems emulators proposals for microgrid laboratory testing platforms. Four emulation conceptual levels are identified based on the literature analysis performed. Each of these levels is explained through a microgrid example, detailing its features and possibilities. Finally, an experimental microgrid, built based on emulators, is presented to exemplify the system performance.

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Section: Resultsmentioning

confidence: 99%

Renewable energy emulation concepts for microgrids

Prieto‐Araujo

Olivella‐Rosell

Cheah-Mañé

et al. 2015

Renewable and Sustainable Energy Reviews

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“…To emulate the wind turbine, the wind turbine emulator proposed in [31] is adoped in this study. In the wind turbine emulator, the power-speed characteristic of a wind turbine is im- plemented by a field-oriented control PMSM servo drive.…”

Section: Wind-turbine Emulatormentioning

confidence: 99%

Radial Basis Function Network Control WithImproved Particle Swarm Optimizationfor Induction Generator System

Lin

Teng

2008

IEEE Trans. Power Electron.

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This study proposes a radial basis function network (RBFN) controlled three-phase induction generator (IG) system using ac-dc and dc-ac power converters. In this study, first, the indirect field-oriented mechanism is implemented for the control of the IG. The electric frequency of the IG is controlled using the indirect field-oriented control mechanism. Then, an ac-dc power converter and a dc-ac power inverter are adopted to convert the electric power generated by a three-phase IG from variable-frequency and variable-voltage to constant-frequency and constantvoltage. Moreover, two on-line trained RBFNs using backpropagation learning algorithm with improved particle swarm optimization (IPSO) are introduced as the regulating controllers for both the dc-link voltage and the ac line voltage of the dc-ac power inverter. The IPSO is adopted in this study to adapt the learning rates in the backpropagation process of the RBFNs to improve the learning capability. By using the proposed RBFN controller with IPSO, the IG system can employ for stand-alone power application effectively. Finally, some experimental results are provided to show the effectiveness of the proposed IG system. Index Terms-Induction generator (IG), particle swarm optimization (PSO), power converter, radial basis function network (RBFN).

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“…Already wide studies have been done to provide an optimum control method [2][3][4][5][6]. In most cases rotor speed, power tracking and power delivery into the grid are controlled by using power converters, direct torque control [7], and stator flux control [8].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic control of matrix-converter-based WECS in order to performance improvement

Khodamoradi

Kargar

Nateghi

2014

2014 22nd Iranian Conference on Electrical Engineering (ICEE)

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This paper describes a new Wind Energy Conversion System (WECS), where fuzzy logic principles and a Matrix Converter (MC) model are used for performance enhancement and efficiency optimization. The MC is used as the interface between the Permanent Magnet Synchronous generator (PMSG) and the grid. The power at the interface with the grid is controlled by MC to ensure that the active power injected into the grid is at its maximum amount. This system has a fuzzy logic controller that tracks the angular frequency with the wind velocity and controls the switching pattern of the matrix converter in order to extract maximum power. The complete control system has been analyzed, and validated by SIMULINK simulation study.

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Intelligent controlled-wind-turbine emulator and induction-generator system using RBFN

Cited by 38 publications

References 21 publications

Renewable energy emulation concepts for microgrids

Renewable energy emulation concepts for microgrids

Radial Basis Function Network Control WithImproved Particle Swarm Optimizationfor Induction Generator System

Fuzzy logic control of matrix-converter-based WECS in order to performance improvement

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