基于WAsP软件复杂山地风电场风资源评估及风机布置优化研究

发布时间：2018-04-25 13:10

本文选题：山地风电 + 改进应用模式　；参考：《中南大学》2014年硕士论文

【摘要】：：风能资源是一种清洁可再生能源,开展风资源利用对促进社会经济可持续发展具有重要作用。某地区风能资源有没有利用价值,需要对该地区风资源的储量进行一个科学的评估。风况分析研究及风资源的评估是风机选型、布置的基础,对推动风资源开发利用都具有重要的意义。论文以内陆中部地区复杂山地风电场作为研究对象,利用风电场区域内已有一年测风资料,针对复杂山地风电场评估及风机布置的局限性,采用模拟预估技术,基于预估软件评估的原理及山地应用误差原因分析,提出对测风站点数据进行估算模型适用订正,旨在探讨通过测风资料的适用订正来改进该预估模式在复杂山地的应用效果；并采用改进粒子群优化算法对风机布置进行了优化研究。本文主要开展了如下研究： 1)基于完整测风数据,经统计分析计算平均风速、风频、风能等风况参数；并利用不同统计算法对Weibull分布参数进行了估计。针对WAsP模式在复杂山地的预估结果超出实际值较大的局限性,论文以测风站点的统计结果对其进行修正处理,修正结果更加贴近实际风况。 2)鉴于预估的修正风速拟合成Weibull分布与WAsP内定模式预估的Weibull分布特性相似,论文采用对测风数据进行WAsP估算模型的适用修正以改进WAsP模式在复杂山地的应用效果；并证明了该WAsP应用改进方式是可行的。 3)基于WAsP改进模式结合SRTM地形高程数据绘制的高分辨率地形图对所研究风电场进行风资源评估,评价该风电场具有风资源开发价值。 4)基于评估结果对复杂山地49.5MW风电场进行风机选型、风机布置及发电量计算；风机选型为Vestas V100/1.8MW,计算风电场理论年发电量为129GWh；扣除尾流折减后电量为114GWh。并采用改进粒子群优化算法对风机布置进行了优化。论文提出的WAsP改进应用方式为复杂山地风资源评估提供了一个更精确的评估应用模式；结合自主开发的优化算法为复杂山地风资源评估研究开发一套完整的评估系统奠定了一定的基础。
[Abstract]:Wind energy resource is a kind of clean and renewable energy, and developing wind resource utilization plays an important role in promoting the sustainable development of social economy. It is necessary to make a scientific assessment of the reserves of wind resources in a certain area. Wind condition analysis and wind resource evaluation are the basis of wind turbine selection and layout, and are of great significance to promote the development and utilization of wind resources. The paper takes the wind farm in the middle of the inland area as the research object, using the wind data of wind farm area for one year, aiming at the limitation of wind farm evaluation and fan layout in the complex mountain area, adopting the simulation and prediction technology. Based on the principle of estimating software evaluation and the analysis of the cause of mountain application error, this paper puts forward the applicable revision of the estimation model for wind station data, in order to discuss how to improve the application effect of the prediction model in the complex mountain area through the application revision of wind data. An improved particle swarm optimization algorithm is used to optimize the fan layout. This paper mainly carried out the following research: 1) based on the complete wind data, the average wind speed, wind frequency and wind energy parameters are calculated by statistical analysis, and the Weibull distribution parameters are estimated by different statistical algorithms. In view of the limitation that the predicted results of WAsP model in complex mountainous areas exceed the actual values, the statistical results of wind survey stations are revised and processed in this paper, and the revised results are more close to the actual wind conditions. 2) in view of the fact that the predicted modified wind speed pseudo synthetic Weibull distribution is similar to the Weibull distribution predicted by WAsP internal model, this paper uses the WAsP estimation model to modify the wind data to improve the application effect of WAsP model in complex mountainous area. It is proved that the improved method of WAsP application is feasible. 3) High resolution topographic map based on WAsP improved mode and SRTM topographic elevation data is used to evaluate wind resources of the wind farm studied, and to evaluate the wind resource development value of the wind farm. 4) based on the evaluation results, the wind turbine selection, fan layout and power generation calculation of complex mountainous 49.5MW wind farm are carried out, the fan selection is Vestas V100- 1.8MWW, and the theoretical annual power generation of wind farm is 129GWh. after deducting the wake reduction, the electricity quantity is 114GWh. An improved particle swarm optimization algorithm is used to optimize the fan layout. The improved application mode of WAsP proposed in this paper provides a more accurate assessment model for the assessment of complex mountain wind resources. Combined with the self-developed optimization algorithm, it lays a foundation for the research and development of a complete evaluation system for the wind resources in complex mountain areas.
【学位授予单位】：中南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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