LIDAR‐assisted radial basis function neural network optimization for wind turbines

Han, Bing; Zhou, Lawu; Zhang, Zhiwen

doi:10.1002/tee.22514

Cited by 13 publications

(11 citation statements)

References 18 publications

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“…In [75], the author proposes an individual pitch controller based on RBFNN. The controller requires two inputs variables, the error in the speed of the rotor axis and the measurement of the wind speed by Light Detection and Range (LIDAR).…”

Section: Van Et Al 2015mentioning

confidence: 99%

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Expert Control Systems for Maximum Power Point Tracking in a Wind Turbine with PMSG: State of the Art

et al. 2019

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Wind power is a renewable energy source that has been developed in recent years. Large turbines are increasingly seen. The advantage of generating electrical power in this way is that it can be connected to the grid, making it an economical and easily available source of energy. The fundamental problem of a wind turbine is the randomness in a wide range of wind speeds that determine the electrical energy generated, as well as abrupt changes in wind speed that make the system unstable and unsafe. A conventional control system based on a mathematical model is effective with moderate disturbances, but slow with very large oscillations such as those produced by turbulence. To solve this problem, expert control systems (ECS) are proposed, which are based on human experience and an adequate management of stored information of each of its variables, providing a way to determine solutions. This revision of recent years, mentions the expert systems developed to obtain the point of maximum power generation in a wind turbine with permanent magnet synchronous generator (PMSG) and, therefore, offers a control solution that adapts to the specifications of any wind turbine.

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Section: Van Et Al 2015mentioning

confidence: 99%

“…Individual pitch controller based on a neural network of radial base function (RBFNN) model, which measures wind speed with light detection and range (LIDAR)[75].…”

mentioning

confidence: 99%

Expert Control Systems for Maximum Power Point Tracking in a Wind Turbine with PMSG: State of the Art

et al. 2019

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“…According to (3), the equivalent impedance modulus of noncritical loads group |Z eq | can be calculated by |V NC | and |I ES |. According to (1) and (11), take the 220 V system with resistive noncritical loads as an example, the range of |V NC | can be expressed as:…”

Section: Research On the Adaptive Voltage-regulation Control Strategymentioning

confidence: 99%

An adaptive voltage‐regulation control strategy of an electric spring based on output current feedback

Chen

Wang

et al. 2018

IEEJ Transactions Elec Engng

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With the increasing penetration of distributed generation (DG) in power systems, the voltage instability problem of power systems is receiving a great deal of attention. As new power electronics equipment, an electric spring (ES) can effectively restrain the bus voltage fluctuation caused by DG, and in addition achieve the new control paradigm of load demand following power generation. In this article, an adaptive voltage‐regulation control strategy of ES is proposed, in which the proportional integral (PI) postgain changes dynamically according to the real‐time output current of the ES. The simulation results show that, when the proposed control strategy is applied, bus voltage can still be stabilized effectively by the ES under the condition that noncritical loads change. The proposed control strategy brings the adaptive voltage‐regulation capability of the ES, and therefore, it can be in series with multiple noncritical loads reliably and safely, and accordingly the costs can be greatly reduced. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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“…Because TLBO has the advantages of few parameters, simple thinking, easy understanding and strong robustness [1][2][3][4], it has attracted the attention of many scholars since it was put forward and has been applied in many fields. Such as reactive power optimization of power system [5], LQR controller optimization [6], IIR digital filter design [7], steelmaking and continuous casting scheduling problem [8], PID controller parameter optimization problem [9,10], feature selection problem [11], HVDC optimization of voltage source converter [12], extension of global optimization technology to constrained optimization [13], analysis of financial time series data [14], neural network optimization [15], etc. Compared with the existing swarm intelligence algorithm, the algorithm obtains better results.…”

Section: Introductionmentioning

confidence: 99%

Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM

Yang

Sun

2020

Front. Phys.

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With the rapid development of vehicle-mounted communication technology, GPS data is an effective method to predict the current road vehicle track based on vehicle-mounted data. GPS-oriented vehicle-mounted data position prediction method is currently a hot research work and an effective method to realize intelligent transportation. In this paper, an improvement scheme is proposed based on the problem of falling into local optimization existing in the basic algorithm of teaching and learning optimization algorithm. An interference operator is used to disturb teachers to enhance the kinetic energy of the population to jump out of local optimization. By comparing the performance of GA, PSO, TLBO, and ITLBO algorithms with four test functions, the results show that ITLBO has efficient optimization effect and generalization ability. Finally, the ITLBO-ELM algorithm has the best prediction effect by comparing the vehicle GPS data and comparing the experimental algorithms.

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LIDAR‐assisted radial basis function neural network optimization for wind turbines

Cited by 13 publications

References 18 publications

Expert Control Systems for Maximum Power Point Tracking in a Wind Turbine with PMSG: State of the Art

Expert Control Systems for Maximum Power Point Tracking in a Wind Turbine with PMSG: State of the Art

An adaptive voltage‐regulation control strategy of an electric spring based on output current feedback

Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM

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