Maximum Output Power Tracking of Wind Turbine Using Intelligent Control

Yuhendri, Muldi; Ashari, Mochamad; Purnomo, Mauridhi Hery

doi:10.12928/telkomnika.v9i2.690

Cited by 13 publications

(8 citation statements)

References 14 publications

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“…The study shows that there is mismatch between the designed and actual plant load factor (PLF), as well as the power generation share of the wind and solar power plant. Fuzzy and neural netrwork generator speed controller is simulated by [9] using Matlab Simulink, the result shows that the both controller was successfully regulates the output power when the wind speed above the wind turbine rated and the output power can be maximum when the wind speed below the wind turbine rated.…”

Section: Introductionmentioning

confidence: 99%

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

et al. 2011

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Abstrak Makalah ini menyajikan analisa karakteristik-karakteristik kecepatan angin di Keywords: weibull distribution function, wind power generation, wind speed IntroductionRenewable energy has an increasing role in achieving the goals of sustainable development, energy security and environmental protection. Nowadays, it has been recognized as one of the most promising clean energy over the world because of its falling cost, while other renewable energy technologies are becoming more expensiveWind energy is one of renewable energy which produced by continuously blowing wind and can be captured using wind turbines that convert kinetic energy from wind into mechanical energy and then into electrical energy [3]. Today, wind energy is widely used to produce electricity in many countries such as Denmark, Spain, Germany, United States, and India [4].A lot of researchers have been studying the wind speed characteristics and its potential as a wind power generation in many countries worlwide. Six kinds of numerical methods for estimating Weibull parameters were reviewed by [5]; i.e. the moment, empirical, graphical, maximum likelihood, modified maximum likelihood, and energy pattern factor method. The result showed that the maximum likelihood modified maximum likelihood and moment methods present relatively more excellent ability throughout the simulation test. From analysis of actual data, it is found that if wind speed distribution matches well with Weibull function, the six methods are applicable, but if not, the maximum likelihood method performs best followed by the modified maximum likelihood and moment methods, based on double checks including

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Section: Introductionmentioning

confidence: 99%

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

et al. 2011

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“…In the I-V curve, there is a point which the power is maximum for a particular irradiation condition. The similar characteristic also occurs in the wind energy system, in the sense that there is a point which a maximum power is achieved for a particular wind speed [3]. Therefore, to achieve the maximum efficiency, it is necessary to track this maximum power point (MPP) called as MPPT (Maximum Power Point Tracking).…”

Section: Introductionmentioning

confidence: 91%

Modeling of Maximum Power Point Tracking Controller for Solar Power System

Soetedjo¹,

Lomi²,

Nakhoda³

et al. 2012

TELKOMNIKA

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“…An electromagnetic torque control strategy adjusting to the mechanical speed to be presented in this part in order to maximize the electrical power generated [15][16][17][18]. This principle is known as terminology (MPPT).…”

Section: Control Of the Wind Turbinementioning

confidence: 99%

Sliding mode performance control applied to a DFIG system for a wind energy production

FatimaZohra

Bendjebbar

Mazari

2020

IJECE

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This project presents a strategy of field control then sliding mode control put in to the conversion process of wind energy containing an asynchronous generator with double fed (DFAG; DFIG). A model was developed for each component of the wind turbine (turbine, DFAG and cascade rectifier-inverter). MPPT device must be introduced in order to obtain maximum energy efficiency so that PI-MPPT method is made. The objective is to apply this command to control independently the active and reactive powers generated by the asynchronous generator uncoupled by orientation from the flow. The results of digital simulations obtained show the improvement of the performances of the sliding control compared to the field control, also it has provided information on the commands available techniques as reference tracking and robustness.

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Maximum Output Power Tracking of Wind Turbine Using Intelligent Control

Cited by 13 publications

References 14 publications

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

Potential of Wind Speed for Wind Power Generation In Perlis, Northern Malaysia

Modeling of Maximum Power Point Tracking Controller for Solar Power System

Sliding mode performance control applied to a DFIG system for a wind energy production

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