Wind Turbine Power Optimization: Experimental Validation of Extremum Seeking and Perturb/Observe Strategies

Author(s):  
Fa Wang ◽  
Laura Wheeler ◽  
Mario Garcia-Sanz

This paper presents an experimental methodology to test and validate two Maximum Power Point Tracking (MPPT) strategies on variable speed wind turbines. The first technique of this study is an Extremum Seeking (ES) control strategy which does not require any wind turbine model or wind speed measurements. The analysis shows that its convergence can be quite slow in some cases. For this reason, we improve the ES control with a specific inner-loop that speeds up the convergence of the strategy. Additionally a conventional Perturb and Observe (P&O) algorithm is also implemented for comparison purposes. The proposed ES strategy with an additional inner loop controller shows fast tracking capability and high stability under both constant and variable wind speed in simulations and experiments. Both approaches are verified in Matlab simulations and experiments with a lab-scale wind turbine and a fully instrumented wind tunnel at CWRU-CESC.

2014 ◽  
Vol 615 ◽  
pp. 426-429
Author(s):  
Shu Yue Lin

Nowadays the application of extremum seeking controller in various engineering industry has attracted a high research attention. Also, it is one of the best known maximum power point tracking algorithm. It can drive the output to its extreme point automatically and dynamically stabilize around the equilibrium. In this paper, it is implemented via Matlab/Simulink. The extremum seeking control scheme controls the wind turbine to operate at its optimal rotational speed adaptively. Piecewise constant input wind will be applied.


Author(s):  
Leiming Ma ◽  
Lingfei Xiao ◽  
Jianfeng Yang ◽  
Xinhao Huang ◽  
Xiangshuo Meng

Aiming at the maximum power point tracking for wind turbine, a sensorless intelligent second-order integral sliding mode control based on wind speed estimation is proposed in this article. The maximum wind energy capture is realized by controlling permanent magnet synchronous motor to adjust the speed of wind turbine. First, an intelligent second-order integral sliding mode control is designed for the speed loop and current loop control, which has fast convergence speed, strong robustness and can effectively reduce chattering. Second, a novel cascade observer based on direct sliding mode observer and extended high-gain observer is used to estimate the rotor speed and position. Besides, combined radial basis function neural network is used to estimate the valid value of wind speed. Both simulation and experiment are implemented, which verify the effectiveness of the proposed strategy under the condition of considering both model uncertainty and external disturbance.


2015 ◽  
Vol 11 (5) ◽  
pp. 50
Author(s):  
Bo Gu ◽  
Liu Yongqian ◽  
Hou Yuxiang ◽  
Kang Shun

A maximum power point tracking (MPPT) algorithm of wind turbines considering wind turbulence characteristics is presented in this paper. The turbulence characteristics of natural wind are analyzed, and the natural wind speed model is established. A MPPT algorithm based on extremum-seeking control (ESC) is proposed, which considers the turbulence characteristics containing in wind speed. The goal of the MPPT algorithm is to keep the wind turbines running at the maximum wind energy utilization coefficient point stably. The algorithm is modeled and analyzed, and the simulation results show that the MPPT algorithm is correct and effective.


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