ADVANCED SIGNAL PROCESSING METHODS APPLIED TO ACOUSTIC WIND PROFILING FOR USE IN WIND FARM ASSESSMENT

据报道，英国的风能潜力高达欧洲全部风能资源的40%。自2003年政府发布可再生能源白皮书以来，风能的开发一直是政治议程上的重要议题，该白皮书确定了风力发电场占能源总量10%的目标。随着对新风场开发的需求不断增加，寻找合适的地点变得更加困难和重要。现在，新的地点都安装了最大容量高达120米的风力涡轮机。考虑到这些设施的成本，评估经济可行性需要高精度的风力测量来预测发电量。目前的标准使用一种叫做杯式风速计的测量技术。这一标准受到质疑已经有一段时间了。由于这些小型仪器需要不易移动的桅杆结构，因此这些数据是否代表拟议的涡轮叶片区域值得怀疑。另一种很有前途的测量方法是使用声脉冲来测量整个风廓线，达到或超过现代风力涡轮机的高度。这些被称为SODARs的仪器主要由一组扬声器组成，可以很容易地在未来的风力发电场周围移动，以测量所有拟议涡轮机位置的剖面。常规SODAR测量的一个主要限制是在普通大气条件下数据丢失。该项目旨在通过调整雷达和声纳技术中常见的信号处理技术来克服这一限制，从而提高数据质量和可用性。这种方法还有望增加概要文件中数据点的数量。在风切变较大的情况下，当叶片上的负荷在叶片直径上不均匀分布时，增强的空间数据分辨率对于风力涡轮机的操作员来说尤为重要。即使信号强度很好，sodar的另一个常见问题是识别雨水和固定物体反射等来源的数据污染。由于大气信号的传播方向与固定回波不同，我们将使用扬声器阵列来定位声音的方向性，从而从噪声中提取信号。首先，我们将在计算机模型中模拟SODAR信号，以评估一些可能的信号处理技术。在项目的第二阶段，我们将在真正的SODAR仪器上实施最有前途的技术。该项目最后将比较新技术与普通SODAR的风廓线，以评估改进的程度。如果成功，该技术可以集成到商用SODAR仪器中。数据质量的提高也有利于其他应用，如空气质量研究、飞机尾流涡探测和危害预防。

The UK wind energy potential is quoted to be as high as 40% of Europe's entire wind resource. Its exploitation has been high on the political agenda ever since the publication of the government whitepaper on renewable energy in 2003, where a target of 10% of energy from wind farms was defined. With the resulting increasing demand for new wind farm developments, the search for suitable sites becomes both more problematic and more important. New sites are now being populated with maximum capacity wind turbines as tall as 120m. Given the cost of such installations, assessing economic viability requires high-precision wind measurements to forecast the power yield. The current standard uses a measurement technology called cup anemometers. This standard has been questioned for some time. As these small instruments require mast structures which cannot be easily moved it is doubtful whether the data are representative for the proposed turbine blade areas. A promising alternative measurement method uses sound pulses to measure an entire wind profile up to and above the heights of modern wind turbines. These instruments, so called SODARs, consist mainly of an array of loudspeakers and are easy to move around a prospective wind farm site to measure profiles at all proposed turbine locations. One major limitation of conventional SODAR measurements is the loss of data under common atmospheric conditions. This project sets out to overcome this limitation by adapting signal processing techniques which are common in RADAR and SONAR technologies to improve data quality and therefore availability substantially. This approach also promises to enhance the number of data points in a profile. The enhanced spatial data resolution can be particularly important for operators of wind turbines in situations with large wind shear when the load on the blades is unevenly spread across the blade diameter. Even when signal strength is good, another common problem with SODARs is to identify data contamination by sources such as rain and reflections from fixed objects. As the atmospheric signal travels in a different direction than the fixed echoes, we will use the loudspeaker array to locate the directionality of the sound to extract the signal from the noise. In a first step we will simulate the SODAR signals in a computer model to evaluate a number of possible signal processing techniques. At stage two of the project we will implement the most promising ones on a real SODAR instrument. The project will conclude with a comparison between the wind profiles of the new technology with those of an ordinary SODAR to evaluate the extent of the improvements. If successful, the technology can be integrated into commercial SODAR instruments. The enhanced data quality can then also benefit other applications such as air quality studies, the detection of aircraft wake vortices and hazard prevention.