scholarly journals Rotational Speed Control Using ANN-Based MPPT for OWC Based on Surface Elevation Measurements

2020 ◽  
Vol 10 (24) ◽  
pp. 8975
Author(s):  
Fares M’zoughi ◽  
Izaskun Garrido ◽  
Aitor J. Garrido ◽  
Manuel De La Sen

This paper presents an ANN-based rotational speed control to avoid the stalling behavior in Oscillating Water Columns composed of a Doubly Fed Induction Generator driven by a Wells turbine. This control strategy uses rotational speed reference provided by an ANN-based Maximum Power Point Tracking. The ANN-based MPPT predicts the optimal rotational speed reference from wave amplitude and period. The neural network has been trained and uses wave surface elevation measurements gathered by an acoustic Doppler current profiler. The implemented ANN-based rotational speed control has been tested with two different wave conditions and results prove the effectiveness of avoiding the stall effect which improved the power generation.

2021 ◽  
Vol 18 (1) ◽  
pp. 11-18
Author(s):  
Adrián Pozo ◽  
Eduardo Muñoz ◽  
Edy Ayala

In the present work, a control strategy for Maximum Power Point Tracking (MPPT) of a wind turbine based on a Doubly Fed Induction Generator (DFIG) is described. This strategy is developed according to the theory of Di-rect Speed Control (DSC) which includes a state observer. This strategy con-siders the Low Shaft Speed (LSS) as an input and the Iqr reference current as the output. This control mechanism allows monitoring the MPPT; thus, changing the Power coefficient (Cp) to its optimal value during the operation of the wind turbine. The controller, among its main features, is configured to work with the incorporation of different wind inputs; fact that permits evaluating the system response to disturbances and variations. For simulations tests, a 1,5 MW wind turbine has been modeled in Matlab and Fatigue, Aero-dynamics, and Structures and Turbulence FAST software. The strategy has been compared to a PI MPPT controller and has demonstrated improvements in terms of speed and output power extraction.


2021 ◽  
Vol 23 (1) ◽  
pp. 45-52
Author(s):  
El Oualid Zouggar ◽  
Souad Chaouch ◽  
Lilia Abdelhamid ◽  
Djaffar Ould Abdeslam

This paper presents a comparative study between two algorithms for controlling the Wind Turbine (WT) using real time platforms: RT-Lab. The Maximum Power Point Tracking (MPPT) control technique is implemented for extracting the maximum energy from the wind. The first control consists in taking as a reference strategy the electromagnetic torque associated with the maximum power curve. This controller is known as Indirect Speed Control (ISC). The second one, based on the measured wind speed, is called Direct Speed Control (DSC). In this second controller, the effectiveness of the controllers was evaluated with a PI controller and a Fuzzy Logic (FL) controller. The performances are analyzed and compared on the OPAL-RT digital simulator, which is based on the RT-LAB platform with the model, and its control built in Simulink. The results of the simulations clearly show that algorithm based on fuzzy controllers gives better performance in terms of monitoring the maximum power coefficient and optimal speed compared to conventional algorithms.


1989 ◽  
Vol 111 (1) ◽  
pp. 53-58 ◽  
Author(s):  
T. Ogawa ◽  
H. Yoshida ◽  
Y. Yokota

An attempt is made here to increase the output of a Savonius rotor by using a flow deflecting plate. When the deflecting plate is located at the optimum position, the rotor power increases nearly 30 percent over that when no deflecting plate is present. The rotor torque was found to become almost zero, when the plate is placed just in front of the rotor. In addition, two systems to control the rotational speed of a Savonius rotor are developed. These permit the rotor to be stopped in strong wind. Operating characteristics of the two control systems are investigated.


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