Correlation of Wind Speed and Wind Turbine Reliability in System Adequacy Assessment

2018 ◽  
Author(s):  
Nga Nguyen ◽  
Saleh Almasabi ◽  
Joydeep Mitra ◽  
Basti Bharath Shenoy
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Adequacy Assessment

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

Evaluation of the influence of wind speed and angle of attack on the aerodynamic effect of wind turbine blades

2017 ◽  
Author(s):  
Salete Alves ◽  
Luiz Guilherme Vieira Meira de Souza ◽  
Edália Azevedo de Faria ◽  
Maria Thereza dos Santos Silva ◽  
Ranaildo Silva
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbine Blades ◽  
Angle Of Attack ◽  
Wind Turbine Blades ◽  
Aerodynamic Effect

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.

scholarly journals Dynamic Loads and Response of a Spar Buoy Wind Turbine with Pitch-Controlled Rotating Blades: An Experimental Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Laboratory Data ◽  
Nonlinear Behavior ◽  
Offshore Wind ◽  
Small Scale ◽  
Wave Steepness ◽  
Design Factor

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.

scholarly journals Dynamic characteristics analysis of planetary gear system with internal and external excitation under turbulent wind load

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110356
Author(s):  
Hexu Yang ◽  
Xiaopeng Li ◽  
Jinchi Xu ◽  
Zemin Yang ◽  
Renzhen Chen
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Nonlinear Dynamic ◽  
Planetary Gear ◽  
Wind Load ◽  
Transmission System ◽  
Gear Transmission ◽  
Stiffness Ratio ◽  
Gear Transmission System ◽  
Planetary Gear System

According to the working characteristics of a 1.5 MW wind turbine planetary gear system under complex and random wind load, a two-parameter Weibull distribution model is used to describe the distribution of random wind speed, and the time-varying load caused by random wind speed is obtained. The nonlinear dynamic model of planetary gear transmission system is established by using the lumped parameter method, and the relative relations among various components are derived by using Lagrange method. Then, the relative relationship between the components is solved by Runge Kutta method. Considering the influence of random load and stiffness ratio on the planetary gear transmission system, the nonlinear dynamic response of cyclic load and random wind load on the transmission system is analyzed. The analysis results show that the variation of the stiffness ratio makes the planetary gear have abundant nonlinear dynamics behavior and the planetary gear can get rid of chaos and enter into stable periodic motion by changing the stiffness ratio properly on the premise of ensuring transmission efficiency. For the variable pitch wind turbine, the random change of external load increases the instability of the system.

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

scholarly journals A Reliability Based Model for Wind Turbine Selection

2013 ◽  
Vol 2 (2) ◽  
pp. 69-74 ◽  
Author(s):  
A.K. Rajeevan ◽  
P.V. Shouri ◽  
Usha Nair
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Point Of View ◽  
Cube Root ◽  
Mathematical Relationship ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
A Site

A wind turbine generator output at a specific site depends on many factors, particularly cut- in, rated and cut-out wind speed parameters. Hence power output varies from turbine to turbine. The objective of this paper is to develop a mathematical relationship between reliability and wind power generation. The analytical computation of monthly wind power is obtained from weibull statistical model using cubic mean cube root of wind speed. Reliability calculation is based on failure probability analysis. There are many different types of wind turbinescommercially available in the market. From reliability point of view, to get optimum reliability in power generation, it is desirable to select a wind turbine generator which is best suited for a site. The mathematical relationship developed in this paper can be used for site-matching turbine selection in reliability point of view.

scholarly journals Enhancing Wind Turbine Power Forecast via Convolutional Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 261
Author(s):  
Tianyang Liu ◽  
Zunkai Huang ◽  
Li Tian ◽  
Yongxin Zhu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Rapid Development ◽  
Superior Performance ◽  
Learning Platform ◽  
Novel Approach ◽  
Wind Power Forecast ◽  
Transformation Methods

The rapid development in wind power comes with new technical challenges. Reliable and accurate wind power forecast is of considerable significance to the electricity system’s daily dispatching and production. Traditional forecast methods usually utilize wind speed and turbine parameters as the model inputs. However, they are not sufficient to account for complex weather variability and the various wind turbine features in the real world. Inspired by the excellent performance of convolutional neural networks (CNN) in computer vision, we propose a novel approach to predicting short-term wind power by converting time series into images and exploit a CNN to analyze them. In our approach, we first propose two transformation methods to map wind speed and precipitation data time series into image matrices. After integrating multi-dimensional information and extracting features, we design a novel CNN framework to forecast 24-h wind turbine power. Our method is implemented on the Keras deep learning platform and tested on 10 sets of 3-year wind turbine data from Hangzhou, China. The superior performance of the proposed method is demonstrated through comparisons using state-of-the-art techniques in wind turbine power forecasting.

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