A new low-cost sensorless MPPT algorithm for small wind turbines

Aubrée, René; Auger, François; Ping, Dai

doi:10.1109/revet.2012.6195288

Cited by 9 publications

(3 citation statements)

References 15 publications

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“…Several studies have concentrated on estimating the curve of Cp through state observers [47][48][49][50][51][52][53][54][55][56][57][58][59][60]. Certainly, wind turbine manufacturers usually provide a Cp curve, but it eventually changes due to mechanical stress, friction or system robustness.…”

Section: Estimators Of Cpmentioning

confidence: 99%

Representation and estimation of the power coefficient in wind energy conversion systems

González-Hernández

Salas-Cabrera

2019

Rev. Fac. Ing.

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This paper aims at summarizing various methods used for representing and estimating the power coefficient in wind turbines, such as exponential, sinusoidal and polynomial models, as well as mathematical tools known as state observers. We present an exhaustive bibliographic review of the models used to calculate the power coefficient, given that this type of studies are scarce nowadays. In addition, we propose models that can be satisfactorily used for various analyzes of wind energy conversion systems, such as the representation by a polynomial function of fourth degree and the models based on the stochastic probability function. The relevance of this work is supported by the advantages and disadvantages of the various models and estimators of the power coefficient, which are presented at the end of the article in a comparative table with the purpose of offering to the reader a general summary. Ultimately, this review aims at helping researchers, students, university professors and those who wish to venture into this field, even though they do not have much experience, to establish a quick synthesized understanding of the different models and representations of the power coefficient.

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Section: Estimators Of Cpmentioning

confidence: 99%

Representation and estimation of the power coefficient in wind energy conversion systems

González-Hernández

Salas-Cabrera

2019

Rev. Fac. Ing.

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“…We are studying a system of energy conversion, it IS therefore interesting to study its energy efficiency [9]. The power supplied at the output of the three phase generator is:…”

Section: A Energy Efficiencymentioning

confidence: 99%

Extended Kalman filter used to estimate speed rotation for sensorless MPPT of wind conversion chain based on a PMSG

Echchaachouai

Hani

Hammouch

et al. 2015

2015 International Conference on Electrical and Information Technologies (ICEIT)

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Ahstract-This paper presents an innovative method of deter mining the value of the optimum wind power employed to design a sensorless Maximum Power Point Tracking (MPPT) algorithm of a wind conversion chain with a Permanent Magnet Synchronous Generator (PMSG) using two estimators: the Extended Kalman Filter (EKF) to estimate rotation speed and the extremum seeking to estimate the coefficient including turbine parameters. The model of Wind Energy Conversion System (WECS) consists of a wind turbine, two-mass drive train, PMSG, and power converter supplying a DC load. The proposed method based on sensorless wind speed, air density and turbine parameters, generates the outputs to be used in the Field Oriented Control (FOC) requiring implementation of an active rectifier and also in the MPPT block.At first, we show the advantage of using a FOC of the PMSG.Then we describe the EKF and the extremum seeking method.Simulations on Matlab-Simulink can be found at the end of the paper, confirming the performance of the proposed approach.

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“…In addition, the pre-programmed characteristic is fixed and hence does not cater for changes which occur over the years. Thus it is recommendable that the MPPT for wind based systems should either be adaptive [1] or independent of the WT characteristic [2,3]. There are three types of MPPT systems in SWTs [2,4]:…”

Section: Introductionmentioning

confidence: 99%

MPPT with Current Control for a PMSG Small Wind Turbine in a Grid-Connected DC Microgrid

Zammit

Staines

Micallef

et al. 2018

Green Energy and Technology

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This paper presents a Maximum Power Point Tracking (MPPT) system for a small wind turbine (SWT) connected to a DC Microgrid under grid-connection conditions. The system consists of a Permanent Magnet Synchronous Generator (PMSG) driven by a SWT which is interfaced to the DC microgrid through a rectification stage and boost converter. The proposed MPPT system is based on the relationship between the DC link power and voltage, which are used to obtain the required inductor current in the Boost converter to provide maximum power output at all wind speeds. The MPPT system, the Boost converter and current control are explained in detail. Simulation of the system operating under varying wind conditions is presented, showing the performance of the developed MPPT algorithm.

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A new low-cost sensorless MPPT algorithm for small wind turbines

Cited by 9 publications

References 15 publications

Representation and estimation of the power coefficient in wind energy conversion systems

Representation and estimation of the power coefficient in wind energy conversion systems

Extended Kalman filter used to estimate speed rotation for sensorless MPPT of wind conversion chain based on a PMSG

MPPT with Current Control for a PMSG Small Wind Turbine in a Grid-Connected DC Microgrid

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