The Intelligent Methods Used in Prediction the Wind Speed and Output Power of Wind Farm

Author(s):  
Xinyan Zhang ◽  
Chongchong Chen ◽  
Weiqing Wang ◽  
Yi Dai
2013 ◽  
Vol 336-338 ◽  
pp. 1114-1117 ◽  
Author(s):  
Ying Zhi Liu ◽  
Wen Xia Liu

This paper elaborates the effect of wind speed on the output power of the wind farms at different locations. It also describes the correction of the power curve and shows the comparison chart of the standard power curve and the power curve after correction. In China's inland areas, wind farms altitude are generally higher, the air density is much different from the standard air density. The effect of air density on wind power output must be considered during the wind farm design.


2014 ◽  
Vol 521 ◽  
pp. 147-150
Author(s):  
Chao Zhong ◽  
Ran Li

This paper used double-fed wind farm as the object. The output power of the double-fed wind farm fluctuates because the wind speed differs and changes and the three-phase shorted to ground fault occurs in the transmission line. The weighted average method was used in double-fed wind farm grid equivalent modeling. By comparing power fluctuations in the actual model and the equivalent model, it is verified the proposed equivalent modeling method is effective.


2009 ◽  
Vol 1 (3) ◽  
pp. 528-538
Author(s):  
M. R. I. Sheikh ◽  
S. M. A. Razzak

In this work, the STATCOM/SMES system with a voltage-source IGBT converter is modeled as a controllable energy source. The objective of the proposed STATCOM/SMES topology is to provide both active and reactive power, which can significantly decrease the voltage and power fluctuations of grid connected fixed speed wind generators. One major problem in wind generator output power smoothing is setting of the reference output power. Constant output power reference is not a good choice because there can be some cases where wind speed is very low and then sufficient power cannot be obtained. In that case, energy storage device can solve the problem but large energy capacity may be needed. To generate output power reference, a Simple Moving Average (SMA) technique is used which corresponds to the energy storage capacity. Thus the capacity of SMES can be small (50% of wind farm capacity). Real wind speed data is used in the simulation analyses, which validates the effectiveness of the proposed control strategy. Keywords: STATCOM/SMES; Energy storage system (ESS); Simple moving average (SMA); Fixed speed wind generator; Voltage source converter (VSC).© 2009 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved.DOI: 10.3329/jsr.v1i3.2605         J. Sci. Res. 1 (3), 528-538 (2009)


Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim

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.


Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 366
Author(s):  
Yang Xia ◽  
Yun Tian ◽  
Lanbin Zhang ◽  
Zhihao Ma ◽  
Huliang Dai ◽  
...  

We present an optimized flutter-driven triboelectric nanogenerator (TENG) for wind energy harvesting. The vibration and power generation characteristics of this TENG are investigated in detail, and a low cut-in wind speed of 3.4 m/s is achieved. It is found that the air speed, the thickness and length of the membrane, and the distance between the electrode plates mainly determine the PTFE membrane’s vibration behavior and the performance of TENG. With the optimized value of the thickness and length of the membrane and the distance of the electrode plates, the peak open-circuit voltage and output power of TENG reach 297 V and 0.46 mW at a wind speed of 10 m/s. The energy generated by TENG can directly light up dozens of LEDs and keep a digital watch running continuously by charging a capacitor of 100 μF at a wind speed of 8 m/s.


2020 ◽  
Vol 12 (6) ◽  
pp. 2467 ◽  
Author(s):  
Fei Zhao ◽  
Yihan Gao ◽  
Tengyuan Wang ◽  
Jinsha Yuan ◽  
Xiaoxia Gao

To study the wake development characteristics of wind farms in complex terrains, two different types of Light Detection and Ranging (LiDAR) were used to conduct the field measurements in a mountain wind farm in Hebei Province, China. Under two different incoming wake conditions, the influence of wind shear, terrain and incoming wind characteristics on the development trend of wake was analyzed. The results showed that the existence of wind shear effect causes asymmetric distribution of wind speed in the wake region. The relief of the terrain behind the turbine indicated a subsidence of the wake centerline, which had a linear relationship with the topography altitudes. The wake recovery rates were calculated, which comprehensively validated the conclusion that the wake recovery rate is determined by both the incoming wind turbulence intensity in the wake and the magnitude of the wind speed.


2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Ping Jiang ◽  
Xiaofei Li ◽  
Yao Dong

With the increasing depletion of fossil fuel and serious destruction of environment, wind power, as a kind of clean and renewable resource, is more and more connected to the power system and plays a crucial role in power dispatch of hybrid system. Thus, it is necessary to forecast wind speed accurately for the operation of wind farm in hybrid system. In this paper, we propose a hybrid model called EEMD-GA-FAC/SAC to forecast wind speed. First, the Ensemble empirical mode decomposition (EEMD) can be applied to eliminate the noise of the original data. After data preprocessing, first-order adaptive coefficient forecasting method (FAC) or second-order adaptive coefficient forecasting method (SAC) can be employed to do forecast. It is significant to select optimal parameters for an effective model. Thus, genetic algorithm (GA) is used to determine parameter of the hybrid model. In order to verify the validity of the proposed model, every ten-minute wind speed data from three observation sites in Shandong Peninsula of China and several error evaluation criteria can be collected. Through comparing with traditional BP, ARIMA, FAC, and SAC model, the experimental results show that the proposed hybrid model EEMD-GA-FAC/SAC has the best forecasting performance.


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