【作者】 纪国瑞；

【导师】 徐大平； 董泽；

【作者基本信息】 华北电力大学（北京） ， 热能工程， 2009， 博士

【摘要】 风力发电技术的研究越来越深入,风电场风速问题的研究是其重要的组成部分。本文在近年国内外关于风电场风速研究成果的基础上,针对风力发电机组控制、风电场运行以及风电机组仿真的需要展开研究,主要工作内容和创新成果如下:1.详细分析了风速特性,针对风力发电机组控制、风电场并网运行和风力发电机组仿真等领域,提炼出风力发电技术中关于风电场风速的三个问题:变速风力发电机组风速软测量,风电场风速预测和短期风速数值模拟。2.由于风速在空间和时间上的随机变化导致风力机风轮在扫风面上所受风速并不一致,风力机所受实际风速无法直接测量。建立了基于支持向量机的变速风力发电机组风速软测量模型,用于估算风力机所受的实际风速。并提出一种融合风速软测量信号的最大风能追踪控制方案。解决了风速样本在线提取、支持向量机在线训练和风速软测量信号与模糊逻辑控制器融合应用等问题。建立的支持向量机风速软测量模型具有很好的效果;融合风速软测量信息的最大追踪控制方案对于快速变化的风速具有更好的跟踪效果,能够更多地捕获风能。3.风电场风速预测是减少风电场并网运行给电网带来不良影响的有效手段。为了提高预测精度,应用可靠分类方法对预测误差进行补偿,取得了较好的效果。该方法能够有效的进行误差补偿,进一步提高了预测结果的精度。4.基于实测数据的实验表明,总体预测精度的提高无法避免单次误差过大。为了避免单次预测误差过大带来的决策风险,提出了一种风电场风速容许区间预测方法。风速容许区间预测不是仅仅给出一个风速的预测值,而是给出一个一定置信水平下的风速值区间。该方法可以根据给定的置信水平得到一个风速容许区间,风速容许区间的半径表征了风速预测结果的可能误差的大小。根据风速容许区间半径的大小采取措施,可以有效的避免某一次预测误差过大带来的决策风险。5.针对风力发电机组仿真的需要,设计了一种应用小波变换在小波域上进行风速谱模拟的方法。首先,对高斯白噪声进行小波分解;然后,根据风速谱密度对各个频段的小波系数进行收缩处理;最后,利用处理过的小波系数重构信号,得到符合一定功率谱密度特性的风速时间序列。通过和已有算法以及实测风速数据的对比表明,该方法得到的风速时间序列能够更好的逼近风速的谱密度特性,能够方便地用于不同场址的风速模拟,更易于工程应用。更多还原

【Abstract】 Wind power technology is more and more in depth study.The research of wind speed in wind farm is an important part of wind power genaration’s study.Based on results of published papers,the main content of this thesis is as follow:1.Analysis of wind speed features is done,and three questions about wind speed in wind farm are epurated aimed at wind power generation technology.The three questions are:wind speed soft sonsor for wind turbin controls,wind speed prediction in wind farm and short term wind speed simulation.2.The effective wind speed for wind turbine can not be measured directly.Soft sensor modeling for effective wind speed was proposed based on support vector regression(SVR),and the effective wind speed was estimated by using the SVR-based model that relates the corresponding variable with other measurements.A max power point track method integrated with wind speed soft sensor is proposed.The problems about wind speed sampling,SVM trainning and the fusion of wind speed infomation and fuzzy logic controller are solved.The proposed method is able to capture more wind energy.3.The primary issue of wind speed forecasting error compensation is the forecasting error estimation.Forecasting error estimation is converted into a samples classification problem in this paper.Firstly,support vector regression model is trained by wind speed time serials;and the analytics of forecasting errors is done with test samples. Secondly,according to the corresponding margin of error of different samples divided into several classes,to facilitate the training of confidence machine.Finally,confidence machine estimates the margin of forecasting errors.Experimental results show that the accuracy and reliability of the classification can be used to reduce the risk of wrong-compensation,and the proposed approach can achieve higher quality of mean hourly wind speed forecasting.4.An approach of wind speed tolerance intervals prediction is proposed.In support vector regression prediction basis,wind speed tolerance intervals are predicted using inductive confidence machine.Wind speed tolerance interval’s width and confidence reflect the accuracy and reliability of the prediction.Compared to pure wind speed forecasting,the accuracy and reliability of the prediction can be used to reduce the risk of decision-making. 5.Short-term wind speed simulation is an important part of wind turbine generation simulation.A wind speed spectrum fitting approach using wavelet transform is proposed. Firstly,Gaussian white noise is decomposed using wavelet transform.Secondly,the wavelet coefficients of every frequency band are shrunk according to the wind speed’s power spectrum.Finally,the wind speed signal is reconstructed using the shrunk wavelet coefficients,and a wind speed time series is proposed.By comparing with other method and real wind speed,it was shown that the proposed approach can approximate the spectral density characteristics of wind speeds more accurate.更多还原