Novel Control Strategy of Wave Energy Converter Using Linear Permanent Magnet Synchronous Generator

Oh, Ye Jun; Park, Joon Sung; Hyon, Byong Jo; Lee, Ju

doi:10.1109/tasc.2018.2799943

Cited by 20 publications

(18 citation statements)

References 10 publications

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“…Herein Optimal learning rate simulations using IPSO algorithm aims to use PMSG for enhancing the overall dynamic response of proposed wave device integration in case of sudden severe load changes or power network failures [30][31][32].…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

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New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems

Hong

Han

et al. 2020

Energies

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In this article, the characteristics of the wave energy converter are considered and a novel dynamic controller (NDC) for a permanent magnet synchronous generator (PMSG) is proposed for Wells turbine applications. The proposed NDC includes a recursive cerebellum model articulation controller (RCMAC) with a grey predictor and innovative particle swarm optimization (IPSO). IPSO is developed to adjust the learning speed and improve learning capability. Based on the supervised learning method, online adjustment law of RCMAC parameters is derived to ensure the system’s stability. The NDC scheme is designed to maintain a supply–demand balance between intermittent power generation and grid power supply. The proposed NDC exhibits an improved power regulation and dynamic performance of the wave energy system under various operation conditions. Furthermore, better results are obtained when the RCMAC is used with the grey predictive model method.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Besides, the inertia weight w is set to 0 and IPSO can reduce parameter settings. Acceleration coefficients c 1 and c 2 can be modified using Equations (29) and (30). These settings are known as time-varying acceleration coefficients and are expressed as follows [29]:…”

Section: Adjust Learning Rates With Ipsomentioning

confidence: 99%

New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems

Hong

Han

et al. 2020

Energies

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“…In Reference 11, an equivalent circuit was presented in order to understand the mechanism of maximum power extraction from the wave. Accordingly, a simple equivalent circuit in the phasor domain is illustrated in Figure 2.…”

Section: System Modelingmentioning

confidence: 99%

“…Also, an SC‐based ESS was adopted to smooth power fluctuations. In Reference 11, the authors proposed damping control for the high‐speed operation of LMPSG‐based WPGS. The authors stated that the damping control improved the extracted power for a wide speed range.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control of direct‐drive wave power generation system connected to DC microgrid through DC cable

Adaryani

Taher

Guerrero

2020

Int Trans Electr Energ Syst

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Wave energy is a renewable energy with a high density. There are different types of wave power generation systems (WPGSs), including Archimedes wave swing (AWS) coupled to a linear permanent magnet synchronous generator. This study proposes a model predictive control (MPC) for AWS‐based WPGS. The predictive current controller is implemented in a generator‐side converter as a substation for proportional integral (PI) controllers with pulse‐width modulation (PWM). Also, a supercapacitor energy storage system with bidirectional DC/DC converter is proposed to maintain DC link voltage stability. A DC/DC converter is used to keep DC microgrid bus voltage at the desired value. The effectiveness of the proposed MPC method is tested at various operating conditions and compared with conventional PI controllers with PWM in the MATLAB/SIMULINK environment.

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“…A nonlinear model predictive control has been implemented and tested by Son and Yeung [18] on a lab-scale permanent-magnet linear generator. A damping control control strategy has been proposed in [19] for high-speed operation of ocean wave energy converter with a linear permanent magnet synchronous generator. In [20], a novel robust model predictive control is presented for application in heaving wave energy converters to maximize the power conversion output while accounting with the device motion constraints.…”

Section: Introductionmentioning

confidence: 99%

Maximum Power Point Tracking for a Point Absorber Device with a Tubular Linear Switched Reluctance Generator

2018

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This paper addresses the control of a Tubular Linear Switched Reluctance Generator (TLSRG) with application in a point absorber device. A maximum power point tracking (MPPT) strategy is proposed to maximize the power extraction from ocean waves. The generator is characterized by average maximum force of 120 kN and a maximum velocity of 1.3 m/s. The proposed MPPT is achieved by changing the generator damping load according to the excitation force induced by a regular wave. A hysteresis controller is applied to regulate the phase current intensity which allows the control of the linear force provided by the generator. The conversion system direct current (DC) bus voltage is adjusted by an isolated DC/DC converter with a proportional integral controller to define the appropriate duty-cycle.

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Novel Control Strategy of Wave Energy Converter Using Linear Permanent Magnet Synchronous Generator

Cited by 20 publications

References 10 publications

New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems

New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems

Model predictive control of direct‐drive wave power generation system connected to DC microgrid through DC cable

Maximum Power Point Tracking for a Point Absorber Device with a Tubular Linear Switched Reluctance Generator

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