Bayesian Inferencing for Wind Resource Characterisation
Bayesian Inferencing for Wind Resource Characterisation
复制标题
风资源表征的贝叶斯推理
DOI：
10.1109/pmaps.2006.360207
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
K. Bell
中科院分区：
文献类型：
--
作者：
M. Miranda;R. Dunn;F. Li;G. Shaddick;K. Bell
风力发电在电力系统中的作用越来越大，这促使人们研究和开发在没有风速数据的地点评估风力资源的方法。应用，如潜在安装的可行性评估和未来情景的系统集成分析，除其他外，可以大大受益于这种方法。本文着重于推断的风速为这些潜在的网站，使用贝叶斯方法来解释的空间分布的资源。为了测试的方法，一年的风速数据从四个气象站建模，并用于推导第五个网站的推论。所使用的方法与模型一起描述，并提出了模拟结果，并与第五个站点的数据进行比较。结果表明，贝叶斯推断可以是一个有用的工具，在风的空间特征
The growing role of wind power in power systems has motivated R&D on methodologies to characterise the wind resource at sites for which no wind speed data is available. Applications such as feasibility assessment of prospective installations and system integration analysis of future scenarios, amongst others, can greatly benefit from such methodologies. This paper focuses on the inference of wind speeds for such potential sites using a Bayesian approach to characterise the spatial distribution of the resource. To test the approach, one year of wind speed data from four weather stations was modelled and used to derive inferences for a fifth site. The methodology used is described together with the model employed and simulation results are presented and compared to the data available for the fifth site. The results obtained indicate that Bayesian inference can be a useful tool in spatial characterisation of wind