A new control strategy for a stand-alone self-excited induction generator driven by a variable speed wind turbine

Deraz, Said A.; Kader, F.E. Abdel

doi:10.1016/j.renene.2012.09.010

Cited by 47 publications

(18 citation statements)

References 9 publications

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“…The nonlinear dynamics of a surface mounted PMSG coupled with PWM voltage source rectifier and PWM dc-to-dc converter (see Figure 1) in the synchronously rotating ( , ) coordinates system is described as follows [38][39][40]…”

Section: Modeling Of Pmsg Associated With Msc and Dc-linkmentioning

confidence: 99%

A Modified RBF Neuro-Sliding Mode Control Technique for a Grid Connected PMSG Based Variable Speed Wind Energy Conversion System

Douanla

Kenné

Pelap

et al. 2018

Journal of Control Science and Engineering

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A modified control scheme based on the combination of online trained neural network and sliding mode techniques is proposed to enhance maximum power extraction for a grid connected permanent magnet synchronous generator (PMSG) wind turbine system. The proposed control method does not need the knowledge of the uncertainty bounds nor the exact model of the nonlinear system. Since the neural network is trained online, the time to estimate good weights can affect the dynamic performance of the process during the startup phase. Therefore an appropriate way to smoothly and explicitly accelerate the neural network rate of convergence during the startup phase is proposed. Furthermore, a flexible grid side voltage source converter control structure which can handle both grid connected and standalone modes based on conventional proportional integral (PI) control method is presented. Simulations are done in Matlab/Simulink environment to verify the effectiveness and assess the performance of the proposed controller. The results analysis shows the superiority of the proposed RBF neuro-sliding mode controller compared to a nonlinear controller based on sliding mode control method when the system undergoes parameter uncertainties.

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Section: Modeling Of Pmsg Associated With Msc and Dc-linkmentioning

confidence: 99%

A Modified RBF Neuro-Sliding Mode Control Technique for a Grid Connected PMSG Based Variable Speed Wind Energy Conversion System

Douanla

Kenné

Pelap

et al. 2018

Journal of Control Science and Engineering

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“…Wind energy conversion systems connected to the utility grid are becoming more rampant in recent years as the world's electricity power demand is growing. Several studies have demonstrated that the installed wind power generation capacity in the world has been increasing at more than 30% per year for the last 10 years [1]. The major advantage of these systems is the abundant availability of the wind power source as compared to conventional energy sources such as natural gas, oil, etc.…”

Section: Introductionmentioning

confidence: 99%

A Simple Flexible and Robust Control Strategy for Wind Energy Conversion Systems Connected to a Utility Grid

Fotso

Kenné

Douanla

2019

Journal of Control Science and Engineering

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This paper presents a simple and robust control strategy for a variable speed wind turbine conversion system using a squirrel-cage induction generator and a three-phase voltage source (AC/DC/AC) Pulse Width Modulation (PWM) converter connected to the utility grid through an LCL filter. The control strategy integrates for the generator side an adaptive radial basis function (RBF) neurosliding mode controller associated with the rotor flux oriented vector control which is used to regulate the turbine rotation speed, rotor flux, and the DC bus voltage. For the grid side, the inverter current and voltage regulation as well as the current injected into the grid are regulated by PI controllers for two modes of operation, namely, the stand-alone mode and grid connected mode. The main contribution of this article is the introduction of a new and simple control algorithm allowing automatic mode switching method based on wind speed. The proposed scheme is very efficient and can be easily implemented in practice. Simulation results illustrate the effectiveness and feasibility of the proposed algorithm.

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“…SEIG appears to be the right candidate to generate electric power for remote area applications [7][8][9][10][11][12][13][14]. It is robust and it can operate in a self-excited mode using only the input mechanical power from the rotating wind turbine.…”

Section: Introductionmentioning

confidence: 99%

Power Management of Islanded Self-Excited Induction Generator Reinforced by Energy Storage Systems

Nasser

Farrag

2018

Energies

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Self-Excited Induction Generators (SEIGs), e.g., Small-Scale Embedded wind generation, are increasingly used in electricity distribution networks. The operational stability of stand-alone SEIG is constrained by the local load conditions: stability can be achieved by maintaining the load's active and reactive power at optimal values. Changes in power demand are dependent on customers' requirements, and any deviation from the pre-calculated optimum setting will affect a machine's operating voltage and frequency. This paper presents an investigation of the operation of the SEIG in islanding mode of operation under different load conditions, with the aid of batteries as an energy storage source. In this research a current-controlled voltage-source converter is proposed to regulate the power exchange between a direct current (DC) energy storage source and an alternating current (AC) grid, the converter's controller is driven by any variation between machine capability and load demand. In order to prolong the system stability when the battery reaches its operation constraints, it is recommended that an ancillary generator and a dummy local load be embedded in the system. The results show the robustness and operability of the proposed system in the islanding mode of the SEIG under different load conditions.

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A new control strategy for a stand-alone self-excited induction generator driven by a variable speed wind turbine

Cited by 47 publications

References 9 publications

A Modified RBF Neuro-Sliding Mode Control Technique for a Grid Connected PMSG Based Variable Speed Wind Energy Conversion System

A Modified RBF Neuro-Sliding Mode Control Technique for a Grid Connected PMSG Based Variable Speed Wind Energy Conversion System

A Simple Flexible and Robust Control Strategy for Wind Energy Conversion Systems Connected to a Utility Grid

Power Management of Islanded Self-Excited Induction Generator Reinforced by Energy Storage Systems

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