A Maximum Power Point Tracking Control Algorithms for a PMSG‐based WECS for Isolated Applications: Critical Review

Belmokhtar, K.; Ibrahim, Hussein; LamineDoumbia, Mamadou

doi:10.5772/63803

Cited by 9 publications

(7 citation statements)

References 93 publications

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“…The input of the WT is wind, and the output is mechanical power that moves the generator rotor. The following formulae for a variable speed wind turbine provide the output mechanical power and torque generated by a wind WT turbine [22].…”

Section: Modelling Of Pmsgmentioning

confidence: 99%

Design and simulation of Hybrid Renewable Energy System for on-grid applications

Antar¹,

Ali²

2022

Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9

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A hybrid renewable energy system (HRES) refers to a system that uses a combination of RESs such as wind and PV solar energies to improve and increase energy production and system efficiency. Since one energy source is used to provide electricity, the other one may be available or unavailable. This study is dealt with the design and analysis of a grid connected HRES conversion based on PV solar and wind turbine energy sources that use a DC converter and a permanent magnet synchronous generator. The goal of this work is to suggest a better dc bus voltage regulation approach for PV/Wind power generation systems that are grid-connected. To get a maximum amount of power generation, a maximum power point tracking controller based on Perturb and Observation algorithm is used. This approach improves efficiency and reduces harmonic content problems. The THD value of the output voltage was 0.94%. The HRES is built and modelled by the MATLAB program.

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Section: Modelling Of Pmsgmentioning

confidence: 99%

Design and simulation of Hybrid Renewable Energy System for on-grid applications

Antar¹,

Ali²

2022

Proceedings of 2nd International Multi-Disciplinary Conference Theme: Integrated Sciences and Technologies, IMDC-IST 2021, 7-9

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“…x i is the input neuron which is speed and y k is the output neuron which is the quadrature axis current and Z inj is the hidden layer represented in the Figure 2 is the connection weight of the input layer. Z j is the output signal and is and is the function of hidden layer Z inj is given by (10). w ok is the bias of output unit and w jk is the connection weight of the output layer.…”

Section: Feed Forward Neural Networkmentioning

confidence: 99%

“…The simpower system in MATLAB is used to simulate the various control algorithms in order to evaluate their efficacy and dynamics. Higher MPP extraction performance was achieved with sensorless FLC controls [10]. Lower order harmonics are reduced on the grid side [11].…”

Section: Introductionmentioning

confidence: 96%

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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“…The blade system converts wind energy to mechanical energy on its shaft. The efficiency of the conversion is represented by ‫ܥ‬ ሺߣ, ߚሻ, namely power coefficient [8,23]. This coefficient is reliant on both pitch angle ߚ and tip speed ratio ߣ [8,24]:…”

Section: A Wind Turbinementioning

confidence: 99%

“…According to [8,23], the coefficient ‫ܥ‬ ሺߣ, ߚሻ versus the tip speed ratio ߣ at different values of ߚ of a typical wind turbine is shown in Figure 2(a) [8,26]. It is easy to see that with a constant pitch angle, the power coefficient ‫ܥ‬ ሺߣሻ reaches a maximum value at an optimal tip speed ratio.…”

Section: A Wind Turbinementioning

confidence: 99%

Smoothing the Power Output of a Wind Turbine Group with a Compensation Strategy of Power Variation

Chung

2021

Eng. Technol. Appl. Sci. Res.

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This paper proposes a new scheme to reduce the output power variation range of a wind turbine group without an energy storage system. This proposal is based on the active power compensation principle for each wind turbine. In this research, the wind turbine operates in the active power control mode. The reference active power is calculated in such a way that it compensates for the difference between the average output power and the actual output power. To verify and evaluate the proposed method, we simulated a group of two 1.5MW-wind turbines in the Simulink environment of MATLAB. Simulation results were compared to the ones of a wind turbine group without any smoothing scheme and the ones of the same group with the Exponential Moving Average method. From this comparison, we can conclude that with the proposed method, the actual output power of the wind turbine group becomes smoother than that of the wind turbine group without any smoothing scheme. Moreover, the performance of the wind turbine group with the proposed method is better than that of the wind turbine group with the Exponential Moving Average method.

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A Maximum Power Point Tracking Control Algorithms for a PMSG‐based WECS for Isolated Applications: Critical Review

Cited by 9 publications

References 93 publications

Design and simulation of Hybrid Renewable Energy System for on-grid applications

Design and simulation of Hybrid Renewable Energy System for on-grid applications

Intelligent approach on sensorless control of permanent magnet synchronous generator

Smoothing the Power Output of a Wind Turbine Group with a Compensation Strategy of Power Variation

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