Performance of wind energy conversion system using a Permanent Magnet Synchronous Generator for maximum power point tracking

Vijayalakshmi, S.; Anuradha, C.; Kovendan, E.; Rattankumar, V.

doi:10.1109/iceteeem.2012.6494482

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…In this manner, the output power of the wind turbine can be varied by adjusting the rotor swept area and by varying the flow conditions, which forms the premise of control of wind energy conversion system . The tip speed ratio λ , is expressed as:

italicTSR = λ = \frac{ωR}{v},

where ω is rotor rotational speed in radian/s and R is the radius of rotor blades in m.…”

Section: Mathematical Model Formulationmentioning

confidence: 99%

Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Varghese

Reji

2019

Int Trans Electr Energ Syst

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Summary This paper proposes a charge controller for ultracapacitor that acts as an energy storage device so that it can minimize the effect of irregular solar radiation and widely varying wind velocity. A suitable supervision for each generating unit and ultracapacitor are mandatory for a standalone system. The primary energy sources solar and wind systems are operating at maximum power point. Adaptive neuro‐fuzzy inference system (ANFIS) is utilized to foresee the voltage of panel at which extreme power is obtained for a solar system and also to ascertain the most extreme power delivered by the nonuniform and unpredictable characteristics of solar and wind energy sources. A common energy management technique is developed to manage the control flow between the distinctive power sources, loads, and ultracapacitor in the system. The results obtained by ANFIS are compared with artificial neural network. A Simulink model of the hybrid standalone system was developed and tested for various insolation, temperature, and wind velocity.

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italicTSR = λ = \frac{ωR}{v},

where ω is rotor rotational speed in radian/s and R is the radius of rotor blades in m.…”

Section: Mathematical Model Formulationmentioning

confidence: 99%

Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Varghese

Reji

2019

Int Trans Electr Energ Syst

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“…You can monitor the generator's actual rotational speed by using the model reference adaptive system. When the wind speed changes, the generator side converter controller at MPP speeds up the generator to deliver the most power possible [19], [20]. The PI, sliding mode controller (SMC), and feed-forward neural network (FFNN) controllers are used in the flux oriented control (FOC) speed control loop.…”

Section: Introductionmentioning

confidence: 99%

Intelligent approach on sensorless control of permanent magnet synchronous generator

Vijayalakshmi

Ganapathy

Anuradha

et al. 2022

IJPEDS

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In this paper, a standalone permanent magnet synchronous generator (PMSG) system is designed to generate power at maximum power point (MPP). The variable speed operation of wind energy conversion system consists of PMSG, controlled rectifier and voltage source inverter co to the load. Proportional integral (PI), sliding mode (SM), and feed forward neural network (FFNN) control strategies are applied in field oriented control (FOC) at generator side converter. A comparative study on power generated at maximum power point (MPP) is done with these controllers using simulation. Hill climb search (HCS) method is applied to attain MPP. Load side inverter control strategy involves the PI and SM controllers in order to maintain the unity power factor and to control the active and reactive power for nonlinear load. The control strategies are modelled and simulated with MATLAB/Simulink. The effectiveness of proposed control method is demonstrated using simulation results.

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Novel MPPT algorithm for low cost wind energy conversion systems

Sl-Subhi

Alsumiri

Alalwani

2017

2017 Intl Conf on Advanced Control Circuits Systems (ACCS) Systems &Amp; 2017 Intl Conf on New Paradigms in Electronics &Amp; I

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Performance of wind energy conversion system using a Permanent Magnet Synchronous Generator for maximum power point tracking

Cited by 3 publications

References 18 publications

Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Energy storage management of hybrid solar/wind standalone system using adaptive neuro‐fuzzy inference system

Intelligent approach on sensorless control of permanent magnet synchronous generator

Novel MPPT algorithm for low cost wind energy conversion systems

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