Wind Turbine Maximum Power Research Articles

Enhancing the maximum power of wind turbine using artificial neural network

Wind energy conversion systems (WECS) now play a significant role in meeting the world's energy needs. Several different approaches are used to try to increase the reliability of these renewable energy systems. Smart systems are designed to be more proactive to improve the performance of renewable energy equipment. Artificial neural networks (ANNs) have a variety of applications, including controlling renewable energy systems. Using optimal torque control (OTC) system based prediction techniques, a controller to monitor a maximum point of wind turbine output power (MPPT) is designed and modeled in this paper. MATLAB/Simulink package tools for neural networks are also used to design the controller and simulate it to achieve the necessary results and to obtain an appropriate analysis for the controller. The results show that the ANN is more active and delivers better output than the traditional controller.

Wind turbine maximum power point tracking control based on unsupervised neural networks

Abstract The main control goal of a wind turbine (WT) is to produce the maximum energy in any operating region. When the wind speed is under its rated value, the control must aim at tracking the maximum power point of the best power curve for a specific WT. This is challenging due to the non-linear characteristics of the system and the environmental disturbances it is subjected to. Direct speed control (DSC) is one of the main techniques applied to address this problem. In this strategy, it is necessary to design a speed controller to adjust the generator torque so to follow the optimum generator speed. In this work, we improve the DSC by implementing this speed controller with a radial basis function neural network (NN). An unsupervised learning algorithm is designed to tune the weights of the NN so it learns the control law that minimizes the generator speed error. With this proposed unsupervised neural control methodology, the electromagnetic torque that allows the optimal power extraction is obtained, and thus the best power coefficient (${C}_\mathrm{p}$) values. The proposal is tested on the OpenFAST non-linear model of the National Renewable Energy Laboratory 1.5 MW WT. Simulation results prove the good performance of this neuro-control approach as it maintains the WT variables into the appropriate range and tracks the rated operation values. It has been compared with the controller included in OpenFAST giving up to 7.87% more power.

A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking

The study in the paper is placed in the broad context of research for increasing the efficiency of capturing and converting wind energy. The purpose of the study is to analyze some mathematical methods for maximum power point tracking in wind turbines. The mathematical methods studied are on–off control, fuzzy control, and neural predictive control. The rules developed for maximum power point tracking are presented. The related control structures and their design methods are presented. The behaviors of the control systems and their energy efficiency are analyzed. Maximum power point tracking ensures a significant increase in the energy generated compared to the unfavorable case of operation at a small and constant load torque. The differences in energy efficiency between the methods of maximum power point tracking studied are small.

Nonlinear Maximum Power Point Tracking Control Method for Wind Turbines Considering Dynamics

A combined strategy of torque error feed-forward control and blade-pitch angle servo control is proposed to improve the dynamic power capture for wind turbine maximum power point tracking (MPPT). Aerodynamic torque is estimated using the unscented Kalman filter (UKF). Wind speed and tip speed ratio (TSR) are estimated using the Newton–Raphson method. The error between the estimated aerodynamic torque and the steady optimal torque is used as the feed-forward signal to control the generator torque. The gain parameters in the feed-forward path are nonlinearly regulated by the estimated generator speed. The estimated TSR is used as the reference signal for the optimal blade-pitch angle regulation at non-optimal TSR working points, which can improve the wind power capture for a wider non-optimal TSR range. The Fatigue, Aerodynamics, Structures, and Turbulence (FAST) code is used to simulate the aerodynamics and mechanical aspects of wind turbines while MATLAB/SIMULINK is used to simulate the doubly-fed induction generator (DFIG) system. The example of a 5 MW wind turbine model reveals that the new method is able to improve the dynamic response of wind turbine MPPT and wind power capture.

Power instability prediction method for wind turbine based on fuzzy decision tree

In order to improve the accuracy and efficiency of power instability prediction for wind turbines, a power instability prediction method for wind turbines based on fuzzy decision tree is proposed. According to the variation curve of maximum output power, the maximum power of wind turbine is searched and controlled by climbing hill. The maximum power of wind turbine is tracked by the control results. The power fluctuation periodicity rule is obtained based on the fuzzy decision tree. The power instability prediction model of wind turbine is established to realize the power instability prediction. The experimental results show that the proposed method has high effectiveness, the highest prediction accuracy can reach 95.53%, and the maximum prediction time is only 1.8 s, which fully shows that the proposed method is more suitable for the power instability prediction of wind turbines.

The impact of humidity on performance of wind turbine

This paper discusses the utilization of a wind energy system as an alternative to traditional sources of energy. It is aimed for studying how to convert kinetic energy from the wind to electrical energy, as well as, the impact of humidity effect on the density of the air. Results of wind speed measured are depended on both solar energy and battery for operating purposes. The frequency of the wind turbine against the wind speed under the climatic conditions of Kirkuk city has been observed. It is found that the maximum value of frequency is at 225° which represented the southern west wind direction then the angle 118° that represented the eastern and southern east along the winter season. It is noted that the maximum value of frequency is at 112.5° which represented the eastern and southern east wind direction then the angle 150° that represented the southern and southern east along the winter season. It was observed that the maximum power of wind turbine reached to 115 W and 148 W for winter and summer season respectively. It is showed that the density of dry air is higher than that of humid air. The humid air implies lower density resulting in lower power from a wind turbine.

Energy Management and Control of Plug-In Hybrid Electric Vehicle Charging Stations in a Grid-Connected Hybrid Power System

The charging infrastructure plays a key role in the healthy and rapid development of the electric vehicle industry. This paper presents an energy management and control system of an electric vehicle charging station. The charging station (CS) is integrated to a grid-connected hybrid power system having a wind turbine maximum power point tracking (MPPT) controlled subsystem, photovoltaic (PV) MPPT controlled subsystem and a controlled solid oxide fuel cell with electrolyzer subsystem which are characterized as renewable energy sources. In this article, an energy management system is designed for charging and discharging of five different plug-in hybrid electric vehicles (PHEVs) simultaneously to fulfil the grid-to-vehicle (G2V), vehicle-to-grid (V2G), grid-to-battery storage system (G2BSS), battery storage system-to-grid (BSS2G), battery storage system-to-vehicle (BSS2V), vehicle-to-battery storage system (V2BSS) and vehicle-to-vehicle (V2V) charging and discharging requirements of the charging station. A simulation test-bed in Matlab/Simulink is developed to evaluate and control adaptively the AC-DC-AC converter of non-renewable energy source, DC-DC converters of the storage system, DC-AC grid side inverter and the converters of the CS using adaptive proportional-integral-derivate (AdapPID) control paradigm. The effectiveness of the AdapPID control strategy is validated through simulation results by comparing with conventional PID control scheme.

Nonlinear observer-based control for PMSG wind turbine

This paper introduces a mechanical sensorless control strategy to be used in variable speed wind energy conversion systems based on permanent magnet synchronous generators. The goal of the control strategy is to track the wind turbine maximum power point. With the proposed strategy, mechanical sensors are not needed to implement the control law. For this reason, electrical sensors -voltage and current sensors-are only needed to build the control law.In order to obtain estimates of the mechanical variables, a nonlinear Luenberger-like observer is designed. This observer only uses measurements of the electrical variables. The estimates are fed back to the controller in order to build the mechanical sensorless control strategy.The performance of the whole system is tested through simulations.

Some Effects of Efficiency on Wind Turbine Interference and Maximum Power Production

The effects of finite efficiency on wake interference and power output are studied for identical horizontal-axis wind turbines in line with the wind. Interference occurs whenever turbines reduce the power available to any turbines downwind of them. The analysis uses wake models that are commonly employed in wind farm layout design. The aerodynamic efficiency is varied from 75% to 100% for six identical hypothetical turbines in line parallel to the wind direction with spacing from four to six rotor diameters. Selfish optimization of the power output of individual turbines and co-operative optimization of the total power are considered. For selfish control, all turbines operate at the maximum possible local C P, based on the aerodynamic efficiency. For co-operative optimization, each turbine operates at a C P value between zero and the selfish value, and the total power is optimized numerically. The results show that at low efficiency, there is little difference in total power output between the two strategies. As efficiency increases, co-operative optimization produces increasingly more power. As turbine spacing increases, the difference between the strategies decreases. There is, however, a realistic range of efficiencies and spacing over which more power is delivered by co-operative optimization. The simplest form of co-operative optimization requires reducing the power output of the most upwind turbine to allow increased performance from those downwind. This should be an easy strategy to implement in wind farm control.

Control Design of Wind Turbine System Using Fuzzy Logic Controller for Middle Voltage Grid

This paper presents a system wind turbine in order to have continously electricity supply for 20 kV grid. Output wind turbine controlled by dc-dc boost converter to produce maximum power in order to obtain the MPP (Maximum Power Point). Output of the converter is controlled by fuzzy logic to obtain the MPP (Maximum Power Point) wind turbine, thus the efficiency wind turbine can be increased. The system of wind turbine is connected to 20 kV grid. From the simulation using matlab 2010 can be conclude that the controller can shift power to 75 % maximum power of wind turbine. DOI: http://dx.doi.org/10.11591/telkomnika.v13i3.7167

Wind Turbine Maximum Power Point Tracking Using FLC Tuned with GA

The pursuit of the MPPT has led to the development of different kinds of controllers, one of which is the Fuzzy Logic Controller, which has proven it's worth. In order to further the advancement, Genetic Algorithms are introduced to give more precise settings to the controller. This work focuses on tuning the MFs of the fuzzy logic system by adapting their width in order to achieve a better result, thereby increasing the energy produced.

Simulation Research on Small Scale Wind Power Generation System Connected to DC Micro-Grid

The small scale wind power generation system is connected to DC micro-grid, which is composed of the small scale wind power generation system, battery, load, DC/AC converter, DC/DC converter, bidirectional DC/DC converter and DC bus. Simulation research is done for the small scale wind turbine model which is connected to the DC micro-grid. The output voltage of boost converter will change in real time by adjusting the PWM duty cycle. The maximum power point of wind power generation system is tracked by using the MPPT(maximum power point tracking) control strategy of perturbation and observation. The simulation results of DC micro-grid show that the tracking of wind turbine maximum power point is normal in the system.

Simulation Comparisons and Implementation of Induction Generator Wind Power Systems

This paper describes the performance comparison of a wind power systems based on two different induction generators as well as the experimental demonstration of a wind turbine simulator for the maximum power extraction. The two induction machines studied for the comparison are the squirrel-cage induction generator (SCIG) and the doubly fed induction generator (DFIG). The techniques of direct grid integration, independent power control, and the droop phenomenon of distribution line are studied and compared between the SCIG and DFIG systems. Both systems are modeled in Matlab/Simulink environment, and the operation is tested for the wind turbine maximum power extraction algorithm results. Based on the simulated wind turbine parameters, a commercial induction motor drive was programmed to emulate the wind turbine and is coupled to the experimental generator systems. The turbine experimental results matched well with the theoretical turbine operation.

Research on Capture the Maximum Wind Energy Base on Fuzzy PID Controller

Abstract:This paper studies the control strategy of doubly-fed wind turbine to capture the maximum wind energy.The maximum wind energy capture is a more important part of the wind generation. Due to random fluctuations of the wind speed, to track the maximum power of wind turbine,we need to constantly adjust the speed of the generator, so that the generation run in the optimal tip speed ratio in different wind conditions,in order to achieve maximum power tracking. In this paper, the stator output indirect control the generator speed to achieve maximum wind energy capture,and decoupling control of active power and reactive power can be achieved.the MATLAB / SIMULINK simulation results verify the correctness and feasibility of this method.

Optimization Design of Wind Turbine Blades Based on BLADED

The optimization of wind turbine blades can increase the generator power and annual output of electricity. Illustrated by the case of 2MW wind turbine, optimizing the blade chord and twist angle by POS algorithm. Modeling by BLADED, analysis the change of lift and drag coefficients, the power coefficient, maximum power of wind turbine, minimum power of wind turbine, wind turbine generating capacity before and after optimization. The results show: the aerodynamic efficiency of optimized blade increased by 4.833 than that before optimization. In the wind speed of 12 m/s (that is lower and normal speed), the average power coefficient is improved by 0.05. The minimum power of the wind turbine increased by 4% -15% .The maximum power of the wind turbine increased by 3% -9%. And the annual production of power increased by 0.25%.

Control of Variable Speed Wind Turbines with Doubly-Fed Induction Generators

The paper presents an overall control method for variable speed pitch controlled wind turbines with doubly-fed induction generators (DFIG). Emphasis is on control strategies and algorithms applied at each hierarchical control level of the wind turbine. The objectives of the control system are: 1) to control the power drawn from the wind turbine in order to track the wind turbine maximum power operation point, 2) to limit the power in case of large wind speeds, and 3) to control the reactive power interchanged between the wind turbine generator and the grid. The present control method is designed for normal continuous operations. The strongest feature of the implemented control method is that it allows the turbine to operate with the optimum power efficiency over a wider range of wind speeds. The model of the variable speed, variable pitch wind turbine with doubly-fed induction generator is implemented in the dynamic power system simulation tool DIgSILENT PowerFactory which allows investigation of the dynamic performance of grid-connected wind turbines within realistic electrical grid models. Simulation results are presented and analysed in different normal operating conditions.