scholarly journals Dynamic response improvement of hybrid system by implementing ANN-GA for fast variation of photovoltaic irradiation and FLC for wind turbine

2015 ◽  
Vol 64 (2) ◽  
pp. 291-314 ◽  
Author(s):  
Maziar Izadbakhsh ◽  
Alireza Rezvani ◽  
Majid Gandomkar
Keyword(s):  
Fuzzy Logic ◽  
Wind Speed ◽  
Dynamic Response ◽  
Wind Turbine ◽  
Hybrid System ◽  
Pitch Angle ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Control Technique ◽  
Power Curves

Abstract In this paper, dynamic response improvement of the grid connected hybrid system comprising of the wind power generation system (WPGS) and the photovoltaic (PV) are investigated under some critical circumstances. In order to maximize the output of solar arrays, a maximum power point tracking (MPPT) technique is presented. In this paper, an intelligent control technique using the artificial neural network (ANN) and the genetic algorithm (GA) are proposed to control the MPPT for a PV system under varying irradiation and temperature conditions. The ANN-GA control method is compared with the perturb and observe (P&O), the incremental conductance (IC) and the fuzzy logic methods. In other words, the data is optimized by GA and then, these optimum values are used in ANN. The results are indicated the ANN-GA is better and more reliable method in comparison with the conventional algorithms. The allocation of a pitch angle strategy based on the fuzzy logic controller (FLC) and comparison with conventional PI controller in high rated wind speed areas are carried out. Moreover, the pitch angle based on FLC with the wind speed and active power as the inputs can have faster response that lead to smoother power curves, improving the dynamic performance of the wind turbine and prevent the mechanical fatigues of the generator

Pitch angle control for grid-connected variable-speed wind turbine system using fuzzy logic: A comparative study

2016 ◽  
Vol 40 (6) ◽  
pp. 528-539 ◽  
Author(s):  
Mouna Ben Smida ◽  
Anis Sakly
Keyword(s):  
Fuzzy Logic ◽  
Wind Speed ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Fuzzy Logic Controller ◽  
Proportional Integral ◽  
Wind Turbine System ◽  
Modeling Uncertainties ◽  
Integral Controller ◽  
Proportional Integral Controller

Pitch angle control is considered as a practical technique for power regulation above the rated wind speed. As conventional pitch control commonly the proportional–integral controller is used. However, the proportional–integral type may well not have suitable performance if the controlled system contains nonlinearities as the wind turbine system or the desired wind trajectory varied with higher frequency. In the presence of modeling uncertainties, the necessity of methods presenting controllers with appropriate performance as the advanced control strategies is inevitable. The pitch angle based on fuzzy logic is proposed in this work. We are interested to the development of a wind energy conversion system based on permanent magnet synchronous generator. The fuzzy logic controller is effective to compensate the nonlinear characteristics of the pitch angle to the wind speed. The design of the proposed strategy and its comparison with a conventional proportional–integral controller are carried out. The proposed method effectiveness is verified using MATLAB simulation results.

Simulating the Dynamic and Steady State Response of a Rotor Resistive Controlled 1.5 MW Variable Speed Wind Turbine

2010 ◽  
Author(s):  
Jared B. Garrison ◽  
Michael E. Webber
Keyword(s):  
Steady State ◽  
Wind Speed ◽  
Dynamic Response ◽  
Wind Turbine ◽  
Power Output ◽  
Pitch Angle ◽  
Maximum Power ◽  
Variable Speed ◽  
Wind Speeds ◽  
Variable Speed Wind Turbine

Currently, wind and solar technologies only generate 0.77% and 0.014% of the U.S. electricity consumption, respectively [1]. Though only a small portion of total U.S. electricity production, both sources have seen significant growth recently. For instance, Texas has more than quadrupled its installed wind capacity over the period from 2005–2009 with new installations totaling over 9400 MW [2, 3]. These two resources are globally available and have the potential to generate massive amounts of electricity. As the amount of installed wind turbines continues to grow, gaining better knowledge of their operation and their dynamic response to changing wind conditions is important to ensure their smooth integration and safe operation. The goal of this research is to analyze the dynamic and steady state operations of a 1.5 MW variable speed wind turbine that uses an external rotor resistive control mechanism. The addition of the external generator rotor resistance allows for adjustment of the generator slip and employs a feedback controller that maintains constant power output at all air velocities between the rated wind speed and cut-out wind speed. Using the electronic programming language PSCAD/EMTDC the model simulates the dynamic response to changing wind conditions, as well as the performance under all wind conditions. The first task of the model was to determine which blade pitch angle produces a maximum power output of 1.5 MW. A sweep was used where the simulation runs over the entire range of wind speeds for a selected pitch angle to find which speed resulted in maximum power output. This sweep was used for numerous blade pitch angles until the combination of wind speed and pitch angle at 14.4 m/s and −0.663°, respectively, resulted in a maximum power of 1.5 MW. The second task was to evaluate the model’s dynamic response to changes in wind conditions as well as steady state operation over all wind speeds. The dynamic response to an increase or decrease in wind speed is important to the safety and life expectancy of a wind turbine because unwanted spikes and dips can occur that increase stresses in the wind turbine and possibly lead to failure. In order to minimize these transient effects, multiple controllers were implemented in order to test each ones’ dynamic response to increasing and decreasing changes in wind velocity. These simulations modeled the characteristics of a variable-speed wind turbine with constant power rotor resistive control. First, through calibrating the model the design specifications of blade pitch and wind speed which yield the peak desired output of 1.5 MW were determined. Then, using the method of controlling the external rotor resistance, the simulation was able to maintain the 1.5 MW power output for all wind speeds between the rated and cutout speeds. Also, by using multiple controllers, the dynamic response of the control scheme was improved by reducing the magnitude of the initial response and convergence time that results from changes in wind speed. Finally, by allowing the simulation to converge at each wind speed, the steady state operation, including generator power output and resistive thermal losses, was characterized for all wind speeds.

Advanced Optimal PSO, Fuzzy and PI Controller with PMSM and WTGS at 5Hz Side of Generation and 50Hz Side of Grid

2016 ◽  
Vol 7 (1) ◽  
pp. 173
Author(s):  
Salam Waley Shneen ◽  
Chengxiong Mao ◽  
Dan Wang
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Control Systems ◽  
Fuzzy Logic Controller ◽  
Energy Content ◽  
Pi Controller ◽  
Dc Bus

To use different control systems, Like Classical PI Controller, Expert System, Fuzzy Logic Controller and Optimization PSO Controller. It used to control for PMSM which worked in integration system to Wind Energy. Wind Energy content of wind turbine, PMSM, Rectifier, DC bus, Inverter, Filter, Load and Grid. In the first step, to run the PMSM with different speeds to get different frequency to selected the frequency in side of generation with the rated speed. Second step, solve the mathematical equation to use different values of wind speed with selected (15,20 m/s and less than with more than 15&20m/s). Third step, Calculation the power generation with wind speed (15 m/5 & 20 m/s). Fourth step, using these component system Rectifier, DC bus, Inverter, Filter, Load & Grid with WTGS & PMSM. Final step, use different control systems, Like Classical PI Controller, Expert System Fuzzy Logic Controller and Optimization PSO Controller With PMSM to analysis all results after using the simulation model of proposed variable speed based WECS. The wind turbine coupled with PMSM.A closed loop control system with a PI control,Fuzzy, PSO in the speed loop with current controllers .The simulation circuits for PMSM, inverter, speed and current controllers include all realistic components of the drive system. These results also confirmed that the transient torque and current never exceed the maximum permissible value.

scholarly journals Improvement of Microgrid Dynamic Performance under Fault Circumstances using ANFIS for Fast Varying Solar Radiation and Fuzzy Logic Controller for Wind System

2014 ◽  
Vol 63 (4) ◽  
pp. 551-578 ◽  
Author(s):  
Maziar Izadbakhsh ◽  
Alireza Rezvani ◽  
Majid Gandomkar
Keyword(s):  
Fuzzy Logic ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Dynamic Performance ◽  
Maximum Power ◽  
Maximum Point ◽  
Maximum Power Point ◽  
Inference System ◽  
Power Point ◽  
Power Curves

Abstract The microgrid (MG) technology integrates distributed generations, energy storage elements and loads. In this paper, dynamic performance enhancement of an MG consisting of wind turbine was investigated using permanent magnet synchronous generation (PMSG), photovoltaic (PV), microturbine generation (MTG) systems and flywheel under different circumstances. In order to maximize the output of solar arrays, maximum power point tracking (MPPT) technique was used by an adaptive neuro-fuzzy inference system (ANFIS); also, control of turbine output power in high speed winds was achieved using pitch angle control technic by fuzzy logic. For tracking the maximum point, the proposed ANFIS was trained by the optimum values. The simulation results showed that the ANFIS controller of grid-connected mode could easily meet the load demand with less fluctuation around the maximum power point. Moreover, pitch angle controller, which was based on fuzzy logic with wind speed and active power as the inputs, could have faster responses, thereby leading to flatter power curves, enhancement of the dynamic performance of wind turbine and prevention of both frazzle and mechanical damages to PMSG. The thorough wind power generation system, PV system, MTG, flywheel and power electronic converter interface were proposed by using Mat-lab/Simulink.

scholarly journals A New Pitch Angle Control Method of Wind Turbine Generators Based on Feedforward Wind Speed Information

2019 ◽  
Vol 122 ◽  
pp. 04001
Author(s):  
Mouayad Sahib ◽  
Thaker Nayl
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Control Method ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Intelligent Control System ◽  
Turbine Generators ◽  
New Strategy

In this work, a new strategy to control the pitch angle of wind turbine generator is proposed. The strategy is based on designing an intelligent control system capable of maintaining a stable minimum fluctuating power generation. This can be achieved by providing the wind speed information to the controller in advance and hence allowing the controller to take the optimum action in controlling the blade pitch angle. A model based optimizer uses Model Predictive Control (MPC) technique to predict the wind turbine generator future behaviour and select the optimal control actions assisted by the wind speed information while satisfying the power generation constraints. The simulation results show that a significant improvement can be made using the proposed control method.

scholarly journals The fuzzy-PID based-pitch angle controller for small-scale wind turbine

2020 ◽  
Vol 11 (1) ◽  
pp. 135
Author(s):  
Quang-Vi Ngo ◽  
Chai Yi ◽  
Trong-Thang Nguyen
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Wind Turbine ◽  
Pitch Angle ◽  
Pid Controller ◽  
Fuzzy Logic Controller ◽  
Small Scale ◽  
Fuzzy Pid ◽  
Proportional Integral Derivative ◽  
Fuzzy Pid Controller

<p>This paper aims to design the pitch angle control based on proportional–integral–derivative (PID) controller combined with fuzzy logic for small-scale wind turbine systems. In this control system, the pitch angle is controlled by the PID controller with their parameter is tuned by the fuzzy logic controller. This control system can compensate for the nonlinear characteristic of the pitch angle and wind speed. A comparison between the fuzzy-PID-controller with the conventional PID controller is carried out. The effectiveness of the method is determined by the simulation results of a small wind turbine using a permanent magnet generator (PMSG).</p>

Stochastic Models of Particle Trajectories in Turbulent Atmosphere Flows by Using the LANGEVIN Equations

Proceedings ◽  
2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Youssra El Qasemy ◽  
Abdelfatah Achahbar ◽  
Abdellatif Khamlichi
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Classical Method ◽  
Degradation Mechanism ◽  
Transformation Process ◽  
Langevin Equations ◽  
Turbulence Data ◽  
Power Curves ◽  
And Diffusion ◽  
Fluctuating Wind

The stochastic behavior of wind speed is a particular characteristic of wind energy production, which affects the degradation mechanism of the turbine, resulting in stochastic charging on the wind turbine. A model stochastic is used in this study to evaluate the efficiency of wind turbine power of whatever degree given fluctuating wind turbulence data. This model is based on the Langevin equations, which characterize, by two coefficients, drift and diffusion functions. These coefficients describe the behavior of the transformation process from the input wind speed to the output data that need to be determined. For this present work, the computation of drift and diffusion functions has been carried out by using the stochastic model to assess the output variables in terms of the torque and power curves as a function of time, and it is compared by the classical method. The results show that the model stochastic can define the efficiency of wind turbine generation more precisely.

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