Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system

Simões, Marcelo Godoy; Bose, B.K.; Spiegel, R.J.

doi:10.1109/28.605737

Cited by 249 publications

(46 citation statements)

References 6 publications

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“…Thus, FLC is a suitable tool for small WECS. Some other notable advantages of the fuzzy logic controller are its simplicity, robustness and computational speed [40]. V Galdi et al [41,42] present a data driven design methodology able to generate a Takagi-Sugeno-Kang (TSK) fuzzy based model for the MPPT operation.…”

Section: Other Intelligent Control Methodsmentioning

confidence: 99%

A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

Sachan

Gupta

Samuel

2017

JGE

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The depleting nature of fossil fuels and the environmental threats have resulted in the emergence of renewable energy sources (RESs) as alternative and accessible energy resources. Amongst various RESs, wind energy is one of the fastest growing distributed energy resources because of its zero-carbon emission and cost efficient generation. Although wind energy is plentiful, it is of intermittent nature, i.e., the wind speed is not constant throughout. So, the strategy followed is to harness maximum output power from this variable wind as when it is available, and various algorithms for maximum power operating point tracking (MPPT) have been proposed and implemented successfully. However, choosing an exact MPPT algorithm for a particular application requires a high degree of skill as each algorithm has its pros and cons. This paper presents a review of various MPPT algorithms suggested in the literature.

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Section: Other Intelligent Control Methodsmentioning

confidence: 99%

A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

Sachan

Gupta

Samuel

2017

JGE

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“…Over the past decade, many different control approaches were used for generators and WT for energy generation [11][12][13][14][15]. In [11], a fuzzy logic control is adopted to control the power of the wind electrical conversion system transmitted to the grid and generator speed.…”

Section: Introductionmentioning

confidence: 99%

“…In [11], a fuzzy logic control is adopted to control the power of the wind electrical conversion system transmitted to the grid and generator speed. The advantage in using a fuzzy logic controller versus a standard proportional-integral (PI) controller, is pointed out in better response to frequently changes in wind speed.…”

Section: Introductionmentioning

confidence: 99%

Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

Lin

2016

Energies

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A permanent magnet (PM) synchronous generator system driven by wind turbine (WT), connected with smart grid via AC-DC converter and DC-AC converter, are controlled by the novel recurrent Chebyshev neural network (NN) and amended particle swarm optimization (PSO) to regulate output power and output voltage in two power converters in this study. Because a PM synchronous generator system driven by WT is an unknown non-linear and time-varying dynamic system, the on-line training novel recurrent Chebyshev NN control system is developed to regulate DC voltage of the AC-DC converter and AC voltage of the DC-AC converter connected with smart grid. Furthermore, the variable learning rate of the novel recurrent Chebyshev NN is regulated according to discrete-type Lyapunov function for improving the control performance and enhancing convergent speed. Finally, some experimental results are shown to verify the effectiveness of the proposed control method for a WT driving a PM synchronous generator system in smart grid.

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“…The rotor speed is also measured and compared to the calculated optimal rotor speed, while the resulting error is used to control a power interface. Implementations of fuzzy-logic-based control systems transferring the maximum power from a wind-energy-conversion system to the utility grid or to a stand-alone system have been presented in [11][12][13] respectively. The controllers are based on a polynomial approximation of the optimal power versus the wind-speed characteristic of the WG.…”

Section: Introductionmentioning

confidence: 99%

High Performance MPPT Based on Variable Speed Generator Driven by Wind Power Generation in Battery Applications

Padmanabhan¹,

Kaliyappan²

2014

Journal of Electrical Engineering and Technology

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-A wind generator (WG) maximum power point tracking (MPPT) system is presented here.It comprises of a variable-speed wind generator, a high-efficiency boost-type dc/dc converter and a control unit. The advantages of the aimed system are that it does not call for the knowledge of the wind speed or the optimal power characteristics and that it operates at a variable speed, thus providing high efficiency. The WG operates at variable speed and thus suffers lower stress on the shafts and gears compared to constant-speed systems. It results in a better exploitation of the available wind energy, especially in the low wind-speed range of 2.5-4.5 m/s. It does not depend on the WG wind and rotorspeed ratings or the dc/dc converter power rating. Higher reliability, lower complexity and cost, and less mechanical stress of the WG. It can be applied to battery-charging applications.

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Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system

Cited by 249 publications

References 6 publications

A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

A Review of MPPT Algorithms Employedin Wind Energy Conversion Systems

Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

High Performance MPPT Based on Variable Speed Generator Driven by Wind Power Generation in Battery Applications

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