稿件没能写出来，向好人请罪 2018年9月，好人 X老师 问我能不能写个稿件。我正好有一个想法，就答应了。 可是，谁成想，近半年一直持续极度过劳，工作效率显著下降。根本抽不出时间来写稿。 计划写的稿件，是讲述一个基本上属于“0到1”的世界领先的原创观点。是一个不仅我国需要，而且具有国际普遍性应用的研究思路。属于风电领域的，具有一定价值的问题。 由于未能及时写出，真傻不仅辜负了好人 X老师 ，而且阻碍了人类的进步。羞愧难当！ 特公开向好人 X老师 请罪。 更糟糕的是，今后3个月内肯定抽不出时间来。 人类的一步有一定意义的进步，就被真傻这样给阻碍了。 相关链接： Miller L M, Brunsell N A, Mechem D B, et al. Two methods for estimating limits to large-scale wind power generation . Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(36): 11169-11174. http://www.pnas.org/content/112/36/11169.full 2019-01-03，2018 年小结（真傻） http://blog.sciencenet.cn/blog-107667-1155092.html 2015-12-23 ， 孙小淳老师《 苏联专家谈中国的“科学文化”》的真实性 http://blog.sciencenet.cn/blog-107667-945476.html 完成任何一项工作，体力的也好，脑力的也好，都需要一定的时间，这个原则乃是不需要证明的定理。 最低限度所必需的几个月时间一直缩短到3-5天这类神奇的数字。 文双春， 2018-07-31 ，看这点就可判断一所大学能否 “一流” 精选 http://blog.sciencenet.cn/blog-412323-1126801.html 一流科学家的共同体会是，一流研究需要时间（ World-class research takes time ），而且需要的是大块连续时间（ large continuous blocks of time ）。科研不像搬砖，搬一块少一块，所以搬一阵歇一阵没关系。科研首先要有新想法，而好不容易冒出来的新想法，从申请项目，到开展研究，直至撰写论文，都需要大把时间。新想法往往娇贵而脆弱，每次打断都像一阵吹翻一屋子卡片的风。研究发现， 一个人在中断片刻后重新专注于一项任务需要约 23 分钟。如果中断时间更长，一个想法可能就随风而去了。 打个比方说，科研就像烧开水，你必须一鼓作气烧到 100 度让它开，否则，你即使烧到 99 度又停一下，它马上又退回到原来的温度了，前功尽弃。 2017-09-07 ， 托尼·施瓦茨（ Tony Schwartz ）：管理能量，而非时间！ http://blog.sciencenet.cn/blog-107667-1074747.html 2015-05-26 ， 哈佛教授告诫你：长期太累太穷，人会变傻！ http://blog.sciencenet.cn/blog-107667-893198.html 穷人不是不努力，而是因为长期贫穷，失去了摆脱贫穷的智力和判断力，这种状况不变，再努力也是白费； 感谢您的指教！ 感谢您指正以上任何错误！
风力发电机的 风速 、风向、 功率 3 个对应时间的 时间序列 一般认为，风速和风向（主要是风速）产生了风力发电机的有功功率输出。实际测量得到的风力发电 机的“风速-功率”关系 图，是具有分散性的一个带子。如下面图片 ： （1）“风速-功率”关系，2015 IEEE，Pai Li，Fig.4 （2）“风速-功率”关系，2015 PNAS，Lee M. Miller，Fig.2.(A) （3）“风速-功率”关系，2014 Lawrence，Wayne Miller，第 4 幅图 我想知道这些带子里有没有进一步的规律性，所以想找到 相同时间点 的测量得到的 风速 、 风向 、 功率 的3个时间序列 。希望时间分辨率小于1分钟的水平（ time resolution ≤ 1 min）。风速变化范围最好能够达到 0~16m/s。 即如下面2个图片所示的数据。 哪有如下两图所示的 相同时间采样 得到的 风速 、 功率 实测数据？ （4）赵瑜，等人，2013，图2 某风场日风速曲线 （5）赵瑜，等人，2013，图3 某风场单台风机日输出功率曲线 相关链接： 赵瑜，周玮，于芃，等．风电有功波动功率调节控制研究 ．中国电机工程学报，2013，33(13)：85-91 http://www.cnki.com.cn/Article/CJFDTotal-ZGDC201313013.htm Li Pai, Guan Xiaohong, Wu Jiang, et al. Modeling dynamic spatial correlations of geographically distributed wind farms and constructing ellipsoidal uncertainty sets for optimization-based generation scheduling . IEEE Transactions on Sustainable Energy, 2015, 6(4): 1594-1605. Miller L M, Brunsell N A, Mechem D B, et al. Two methods for estimating limits to large-scale wind power generation . Proceedings of the National Academy of Sciences of the United States of America, 2015, 112(36): 11169-11174. http://www.pnas.org/content/112/36/11169.full Lawrence Livermore National Laboratory, Arnie Heller, april 2014, Predicting Wind Power with Greater Accuracy Researchers are combining fieldwork, advanced simulation, and statistical analysis to help wind farm and electric power grid operators. https://str.llnl.gov/april-2014/miller Wind turbine manufacturers typically provide operators with a simple “power curve,” which shows power from the turbine as primarily the cube of hub-height wind speed. However, Livermore researchers are showing that power curves frequently err by ± 20 percent of actual power output, as seen in this plot of observed power versus wind speed at a northern California wind farm. The color map relates atmospheric stability conditions to reported power-output observations. Eastern Wind Dataset http://www.nrel.gov/electricity/transmission/eastern_wind_methodology.html The Eastern Wind Dataset contains modeled wind farm data points for the eastern United States for 2004, 2005, and 2006. It is intended for use by energy professionals such as transmission planners, utility planners, project developers, and university researchers who perform wind integration studies and estimate power production from hypothetical wind plan. 感谢您的指教！ 感谢您指正以上任何错误！
【按: 现代风力发电场通常由排列成阵列的多个风力涡轮机组成 , 这其中产生的尾流干扰反过来会影响风力涡轮机的发电效率 , 如何抑制尾流干扰 , 是提高风电场发电效率的关键 . 相比传统的单转子风力涡轮机 , 本文介绍了一种串联式反向旋转风力涡轮机系统 , 并在爱荷华州立大学一个大型的空气动力学 / 大气边界层 (AABL) 风洞进行了实验研究 . 结果表明 , 串联式反向旋转风力涡轮机系统可以有效的抑制尾流干扰 , 并显著提高风力涡轮机的发电效率 , 最高达到 20%. 】 Wind energy is one of the most promising renewable energy resources in the world today. Dr. Hui Hu and his group at Iowa State University studied the effects of the relative rotation directions of two tandem wind turbines on the power production performance, the flow characteristics in the turbine wake flows, and the resultant wind loads acting on the turbines. The experimental study was performed in a large-scale Aerodynamics/Atmospheric Boundary Layer (AABL) Wind Tunnel available at Aerospace Engineering Department of Iowa State University. Their work, entitled “An experimental study on the effects of relative rotation direction on the wake interferences among tandem wind turbines”, was published recently in SCIENCE CHINA Physics, Mechanics Astronomy, 2014, Vol 57(5). In a typical wind farm, the wind turbine located in the wakes of upstream turbines would experience a significantly different surface wind compared to the ones located upwind due to the wake interferences of the upwind turbines. Depending on the wind turbine array spacing and layout, the power losses of downstream turbines due to the wake interferences were found to be up to 40%. Therefore, how to improve the power production of downstream wind turbines in a wind farm is one of the most significant research topics in recent years. Extensive experimental and numerical studies have been conducted recently to examine wind turbine aeromechanics and wake interferences among multiple wind turbines in order to gain insight into the underlying physics for higher total power yield and better durability of the wind turbines. While most of the wind turbines in modern wind farms are Single Rotor Wind Turbine (SRWT) systems, the concept of Counter-Rotating Wind Turbine (CRWT) systems has been suggested in recent years. Since azimuthal velocity would be induced in the wake flow behind a wind turbine with its rotation direction in the opposite direction to the upstream rotor, the downstream rotor should rotate in the same direction as the swirling wake flow for a CRWT system in order to extract wind energy in the wake flow more efficiently. So far, since the distance between the two rotors in a CRWT system is always very small (i.e., less than 1 D, and D is the rotor diameters), the attempts of CRWT to improve wind energy utilization are focused on near wake characteristics. On the other hand, most of the previous studies on the wake interferences among multiple turbines are limited to SRWT systems with all the turbines rotating in the same direction. The wake interferences among SRWT systems with different rotation directions in a wind farm have never been investigated before. With this in mind, Dr. Hu and his group conducted a comprehensive experimental study to quantify the effects of the relative rotation direction of two tandem wind turbines on the wake interferences among the turbines. While the oncoming flow was kept constant during the experiments, the model turbines were set to operate in either co-rotating (i.e., the downstream turbine has the same rotation direction as the upstream turbine) or counter-rotating (i.e., the downstream turbine has an opposite rotation direction in relation to the upstream turbine) configuration. The turbine power outputs, the static and dynamic wind loads (i.e., aerodynamic forces and bending moments) acting on the turbines, and the turbulence characteristics in the wake flows behind the turbines were measured and compared quantitatively. It was found that the turbines in counter-rotating would harvest more wind energy from the same oncoming wind, compared with the co-rotating case. While the recovery of the streamwise velocity deficits in the wake flows was found to be almost identical with the turbines operated in either co-rotating or counter-rotating, the significant azimuthal velocity generated in the wake flow behind the upstream turbine is believed to be the reason why the counter-rotating turbines would have a better power production performance. Since the azimuthal velocity in the wake flow was found to decrease monotonically with the increasing downstream distance, the benefit of the counter-rotating configuration was found to decrease gradually as the spacing between the turbines increases. While the counter-rotating downstream turbine was found to be able to produce up to 20% more power compared with the co-rotating downstream turbine when the spacing between the turbines was 0.7 rotor diameters (i.e., 0.7 D ), the advantage of the counter-rotating configuration was found to be reduced to only about 4.0% when the spacing between the turbines was increased to about 5.0 D . Since the azimuthal flow velocity in the wake flow was found to become almost negligible in the further downstream region, the benefits of the counter-rotating configuration were found to die away (i.e., 1.0%) when the spacing between the turbines becomes greater than 6.5 D . It suggests that, on the practical relevance of wind farm design, counter-rotating configuration would be more beneficial to onshore wind farms, compared with offshore wind farms, due to the much smaller spacing between the turbines (i.e., ~3 rotor diameters for onshore wind farms vs. 6~10 rotor diameters for offshore wind farms), especially for those turbines sited over the mountains/hills with the spacing between the turbines only about 1~2 rotor diameters. Figure 1 The ratios of the power outputs for the downstream turbine in counter-rotating to those in co-rotating as a function of the spacing between the turbines See the article: Yuan W, Tian W, Ozbay A, Hu H. An experimental study on the effects of relative rotation direction on the wake interferences among tandem wind turbines. Sci China-Phys Mech Astron, 2014, 57(5): 935-949, doi: 10.1007/s11433-014-5429-x 订阅《中国科学: 物理学 力学 天文学》微信公众号，手机同步关注最新热点文章、新闻、科技资讯, 请添加微信号 SCPMA2014 或扫描下方图片关注.
标签: 风电
