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ELE
- 双馈电机变速恒频发电原理 通过对风力机转速的控制，可以实现最大功率点跟踪，尽量多地吸收风能；而调节无功功率可以控制向电网输出的功率因数，也可提高风电机组及电网系统的动、静态运行稳定性-VSCF doubly-fed electrical power through the principle of wind turbine speed control, maximum power point tracking can be ach
fengdiangonglv
- 对风电功率的预测 时间序列预测 卡尔曼滤波预测 -Prediction of wind power time series prediction Kalman filter prediction
shijianxulie-GP
- 风电功率的预测程序，matlab做的，可运行，基于时间序列-Wind power forecasting process, and do Matlab can be run based on time series
1
- 全功率风电变频器 设计资料 很有用的参考资料-full power windpower inverter design it will beuseful to you
Wind-power-prediction-problem
- 利用新陈代谢灰色预测、样本自适应BP 神经网络和时间序列分析分别进行风电功率实时预测和日前预测，并采用熵值取权法确定组合权重，引入自控机制，构建反馈，提出组合预测法和基于时间序列的卡尔曼滤波法。研究结果表明，组合预测模型能减少各预测点较大误差的出现，而卡尔曼滤波能大幅消减原始序列的波动影响。-Use of metabolic gray forecast, sample adaptive BP neural network and tim
ARIMA
- ARIMA 时间序列法预测未来一段时间的风速或者风电功率-wind prediction
Time-series-neural-network
- 运用神经网络与时间序列分析对风电功率进行预测的一个matlab程序。-Using neural network and time series analysis forecast wind power
lamudacpcalculatetest
- 风电功率系数的计算，应用经验公式，计算风力机吸收功率的系数-calculate coefficient of wind power
windspeedsvm1
- 利用支持向量机进行风速的预测，从而被风力发电所利用，挺高风电功率预测的可靠性-Using support vector machines for wind speed prediction, which was exploited by wind power, wind power prediction pricey reliability
prediction-of-weather-data
- 用BP神经网络和rbf神经网络预测风电功率-BP neural network and rbf neural network forecasting wind power
artificial-neural-network-method
- 基于人工神经网络法的风电功率预测matlab程序，可预测未来几十个小时内的风电功率。-Based on Artificial Neural Network Method wind power prediction matlab program, you can predict the future of dozens of hours of wind power.
time-series-method
- 基于时间序列法的风电预测matlab程序，可根据已知数据预测未来的风电功率。-Method based on time series prediction matlab program for wind power, according to known data to predict the future wind power.
gray-model
- 基于灰色模型的风电预测matlab程序,根据已有数据利用灰色模型预测未来的风电功率。-Wind power based on gray model prediction matlab program, based on the existing data using gray models to predict the future wind power.
MyBP-lxf
- 基于NWP数据和BP-人工神经网络的超短期风电功率预测-Based on NWP data and BP-ANN ultra short-term wind power prediction
svm
- 风电功率预测，通过改进的支持向量机模式进行预测，(wind power prediction)
pp22
- 采用小波变换对风电功率进行分解，然后基于ARMA对风电功率进行短期预测(Wavelet transform decomposition wind power, then ARMA based on short-term wind power prediction)
wind power forecasting based on EWT-KELM
- 针对短期风电功率预测，提出一种基于经验小波变换预处理的核极限学习机组合预测方法。首先采用 EWT 对风电场实测风速数据进行自适应分解并提取具有傅立叶紧支撑的模态信号分量，针对每个分量分别构建 KELM 预测模型，最后对各个预测模型的输出进行叠加得到风速预测值并根据风电场风功特性曲线可得对应风电功率预测值。(Aiming at short-term wind power prediction, a kernel-based learnin
蒙特卡罗
- 基于时序蒙特卡洛的风电可靠性分析代码，可以计算风力发电机发出的功率，LOLP和EENS(Based on the time series Monte Carlo code for wind power reliability analysis, the power generated by wind turbines, LOLP and EENS can be calculated.)
pso优化BP
- 使用pso优化神经网络，使风电功率预测达到更高的精度(a pso algorithm used to optmize bp neural network)
LSSVM
- 结合风场实时数据以及风场气象数据，分析了实时数据并制定了数据清洗规则；针对风电功率预测领域预测精度低的问题，采用lssvm算法进行预测。(Combined with real-time wind field data and wind field meteorological data, the real-time data was analyzed and data cleaning rules were formulated. Fo