Wind Speed Forecasting Based on Data Mining in Wind Farm

机译：基于数据挖掘的风电场风速预测

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Wind speed forecasting plays a significant role in the operation of wind power plants and power systems.An accurate forecasting on wind speed can effectively relieve or avoid the negative impact of wind power plantson power systems and enhance the competition of wind power plants in electric power market. Based on datamining,a method of wind speed forecasting is presented in this paper. By mining historical data as the learningstylebook using the fuzzy neural network (FNN),we can forecast the wind speed. The simulation results showthat this method can improve the accuracy of wind speed forecasting effectively.

机译：风速预测在风力发电厂和电力系统的运行中发挥着重要作用，准确的风速预测可以有效缓解或避免风力发电厂对电力系统的负面影响，并增强风力发电厂在电力市场中的竞争力。基于数据挖掘，提出了一种风速预测方法。通过使用模糊神经网络（FNN）提取历史数据作为学习样式书，我们可以预测风速。仿真结果表明，该方法可以有效提高风速预报的准确性。

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来源
《Proceedings of the 4th International Conference on Intelligent Logistics Systems》|2008年|145-151|共7页
会议地点 Shanghai(CN);Shanghai(CN)
作者
J.S.Olsen; rnZ.L.Zhang; rnC.van der Eijk;
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作者单位

Cuiru Wang@School of Computer Science,North China Electric Power University,Mailbox 330,Baoding 071003,China--Qile Wang@School of Computer Science,North China Electric Power University,Mailbox 330,Baoding 071003,China--Huawei Mei@School of Computer Science,North China Electric Power University,Mailbox 330,Baoding 071003,China--;

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原文格式 PDF
正文语种 eng
中图分类物资流通;
关键词
wind power generation; wind speed forecasting; data mining; FNN.;

机译：风力发电;风速预测;数据挖掘; FNN;

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专利

1. AN INTEGRATED WIND POWER FORECASTING METHODOLOGY: INTERVAL ESTIMATION OF WIND SPEED, OPERATION PROBABILITY OF WIND TURBINE,AND CONDITIONAL EXPECTED WIND POWER OUTPUT OF A WIND FARM [J] . Heping Liu, Jing Shi, Ergin Erdem International journal of green energy . 2013,第1a5期

机译：一种集成的风电功率预测方法：风速的区间估计，风轮机的运行概率以及有条件的风电场功率输出
2. Ensemble interpolation of missing wind turbine nacelle wind speed data in wind farms based on robust particle swarm optimized generalized regression neural network [J] . Du Jie, Sun Hongchuan, Cao Yijia, International journal of green energy . 2019,第11a15期

机译：基于强大的粒子群优化的广义回归神经网络，风电场中缺失风力涡轮机Nacelle风速数据的集合插值
3. A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm [J] . Neshat M., Alexander B., Wagner M., Energy Conversion & Management . 2021,第May期

机译：基于深度学习的短期风速预测演化模型 - 以卢尔德鲁德海上风电场为例
4. Wind Speed Forecasting Based on Data Mining in Wind Farm [C] . International Conference on Intelligent Logistics Systems . 2008

机译：基于风电场数据挖掘的风速预测
5. Short-term forecasting of wind speed and wind power based on BP and Adaboost_BP. [D] . Mi, Sibei. 2014

机译：基于BP和Adaboost_BP的风速和风能的短期预测。
6. Datasets on hub-height wind speed comparisons for wind farms in California [O] . Meina Wang, Paul Ullrich, Dev Millstein 2018

机译：加利福尼亚风电场的轮毂高度风速比较数据集
7. Short-Term Wind Speed Forecasting Based on Information of Neighboring Wind Farms [O] . Zhongju Wang, Jing Zhang, Yu Zhang, 2020

机译：基于邻近风电场信息的短期风速预测

Wind Speed Forecasting Based on Data Mining in Wind Farm

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