Optimal Control of a Wind Turbine for Tradeoff Analysis Between Energy Harvesting and Noise Emission

2013 ◽  
Author(s):  
Mohamed L. Shaltout ◽  
Dongmei Chen
Keyword(s):  
Optimal Control ◽  
Energy Harvesting ◽  
Wind Turbine ◽  
Load Condition ◽  
Noise Emission ◽  
Continuous Growth ◽  
Control Approach ◽  
The Public ◽  
Partial Load ◽  
Blade Pitch Angle

An optimal control approach for a wind turbine drivetrain with the objective of maximizing energy harvesting and minimizing noise emission is presented. One of the major challenges facing the public acceptance for continuous growth of wind turbine installation is its noise emission. However, reducing the noise emission could lead to decreased wind energy harvesting. As a result, a tradeoff arises between power generation and noise emission, especially when a wind turbine operates under the partial-load condition. This paper will show that through controlling the generator electromagnetic torque and/or the blade pitch angle, an optimal tradeoff between wind turbine energy harvesting and noise emission can be obtained. The dynamic model of a wind turbine drivetrain and a noise emission prediction model are also presented. Simulation results of using the proposed control design for different wind speed ranges are analyzed and compared.

scholarly journals Variational Control Approach to Energy Extraction from a Fluid Flow

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4913
Author(s):  
Gianluca Pepe ◽  
Federica Mezzani ◽  
Antonio Carcaterra ◽  
Luca Cedola ◽  
Franco Rispoli
Keyword(s):  
Optimal Control ◽  
Fluid Flow ◽  
Energy Harvesting ◽  
Control Theory ◽  
Wind Turbine ◽  
Optimal Control Theory ◽  
Maximum Efficiency ◽  
Time Interval ◽  
Electrical Machine ◽  
Control Approach

Energy harvesting from the environment is an important aspect of many technologies. The scale of energy capturing and storage can involve the power range from mWatt up to MWatt, depending on the used devices and the considered environments (from ambient acoustic and vibration to ocean wave motion, or wind). In this paper, the wind turbine energy harvesting problem is approached as an optimal control problem, where the objective function is the absorption of an amount of energy in a given time interval by a fluid-flow environment, that should be maximized. The interest relies on outlining general control models of fluid-flow-based extraction plants and identifying an optimum strategy for the regulation of an electrical machine to obtain a maximum-efficiency process for the related energy storage. The mathematical tools are found in the light of optimal control theory, where solutions to the fundamental equations are in the frame of Variational Control (the basis of the Pontryagin optimal control theory). A special problem, named Optimally Controlled Betz’s Machine OCBM-optimal control steady wind turbine, is solved in closed form, and it is shown that, in the simpler steady case, it reproduces the maximum efficiency machine developed in Betz’s theory.

Optimal Control of a Wind Turbine With a Variable Ratio Gearbox for Maximum Energy Capture and Prolonged Gear Life

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Mohamed L. Shaltout ◽  
John F. Hall ◽  
Dongmei Chen
Keyword(s):  
Optimal Control ◽  
Wind Energy ◽  
Wind Turbine ◽  
Gear Tooth ◽  
Tangential Force ◽  
Maximum Energy ◽  
Variable Ratio ◽  
New Approach ◽  
Control Approach ◽  
Energy Capture

An optimal control approach for a wind turbine drivetrain with a variable ratio gearbox is presented. The objective is to find the optimum shifting sequence of the variable ratio gearbox in order to maximize power generation and extend gear life. The employment of a variable ratio gearbox enhances the capabilities of the wind turbine to cope with wind speed variations. Based on the authors' preliminary study, the gear ratios of the variable ratio gearbox were carefully selected to maximize the wind energy capture. In this paper, a new control approach is proposed to achieve both extended gear service life and optimal energy harvesting. This new approach finds the gear shifting sequence that will minimize the tangential force on the gear tooth while maximizing the wind energy capture. The wind turbine drivetrain with a variable ratio gearbox is modeled and simulation results based on recorded wind data of different wind classes are presented and compared.

scholarly journals Optimal Control of the Positional Electric Drive and Its Implementation

Machines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 70
Author(s):  
Vladimir Dotsenko ◽  
Roman Prokudin ◽  
Alexander Litvinenko
Keyword(s):  
Optimal Control ◽  
Wind Turbine ◽  
Electric Drive ◽  
Minimum Energy ◽  
Air Gap ◽  
Synchronous Generators ◽  
Capacitor Discharge ◽  
Wind Speeds ◽  
Minimum Energy Consumption ◽  
Low Wind Speeds

The article deals with the optimal control of the positional electric drive of the stator element of a segment-type wind turbine. The calculation options charts current in the assumption of the minimum energy consumption and the implementation of line chart current using the phenomenon of capacitor discharge. The analysis of the implementation is expressed in a jump-like change in current and a triangular graph of the speed change. This article deals with small capacity synchronous wind turbine generators with a segment type stator. These units have the possibility of intentionally changing the air gap between the rotor and stator. This allows: (1) Reduce the starting torque on the rotor shaft, which will allow the rotor to pick up at low wind speeds. (2) Equivalent to change of air gap in this case is change of excitation of synchronous generators. Thus, the purpose of the article is to consider a method of excitation of generators in a segmented design, by controlling the gap with the electric drive, while providing control should be carried out with minimal losses.

scholarly journals Optimal Pressure Boundary Control of Steady Multiscale Fluid-Structure Interaction Shell Model Derived from Koiter Equations

Fluids ◽  
2021 ◽  
Vol 6 (4) ◽  
pp. 149
Author(s):  
Andrea Chierici ◽  
Leonardo Chirco ◽  
Sandro Manservisi
Keyword(s):  
Optimal Control ◽  
Solid Wall ◽  
Fluid Structure Interaction ◽  
Computational Cost ◽  
Robin Boundary Condition ◽  
Design Parameters ◽  
Fluid Structure ◽  
Control Approach ◽  
Structure Interaction ◽  
Fluid Boundary

Fluid-structure interaction (FSI) problems are of great interest, due to their applicability in science and engineering. However, the coupling between large fluid domains and small moving solid walls presents numerous numerical difficulties and, in some configurations, where the thickness of the solid wall can be neglected, one can consider membrane models, which are derived from the Koiter shell equations with a reduction of the computational cost of the algorithm. With this assumption, the FSI simulation is reduced to the fluid equations on a moving mesh together with a Robin boundary condition that is imposed on the moving solid surface. In this manuscript, we are interested in the study of inverse FSI problems that aim to achieve an objective by changing some design parameters, such as forces, boundary conditions, or geometrical domain shapes. We study the inverse FSI membrane model by using an optimal control approach that is based on Lagrange multipliers and adjoint variables. In particular, we propose a pressure boundary optimal control with the purpose to control the solid deformation by changing the pressure on a fluid boundary. We report the results of some numerical tests for two-dimensional domains to demonstrate the feasibility and robustness of our method.

scholarly journals Adaptive Optimal Robust Control for Uncertain Nonlinear Systems Using Neural Network Approximation in Policy Iteration

2021 ◽  
Vol 11 (5) ◽  
pp. 2312
Author(s):  
Dengguo Xu ◽  
Qinglin Wang ◽  
Yuan Li
Keyword(s):  
Neural Network ◽  
Optimal Control ◽  
Robust Control ◽  
Nonlinear Systems ◽  
Policy Iteration ◽  
Control Law ◽  
Globally Asymptotically Stable ◽  
Control Approach ◽  
Input Uncertainties ◽  
Theoretical Results

In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust control is converted into solving an optimal control containing a nominal or auxiliary system with a predefined performance index. It is demonstrated that the optimal control law enables the considered system globally asymptotically stable for all admissible uncertainties. Second, based on the Bellman optimality principle, the online PI algorithms are proposed to calculate robust controllers for the matched and the mismatched uncertain systems. The approximate structure of the robust control law is obtained by approximating the optimal cost function with neural network in PI algorithms. Finally, in order to illustrate the availability of the proposed algorithm and theoretical results, some numerical examples are provided.

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