An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
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DOI：
10.1016/j.apenergy.2015.10.145
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发表时间：
2016-01
期刊：
影响因子：
11.2
通讯作者：
J. Zhao;Zhen-hai Guo;Zhongyue Su;Zhiyuan Zhao;X. Xiao;Feng Liu
中科院分区：
文献类型：
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作者：
J. Zhao;Zhen-hai Guo;Zhongyue Su;Zhiyuan Zhao;X. Xiao;Feng Liu
准确的风速预报对风能资源的安全利用有很大影响，仍然是一个关键问题和巨大挑战。目前，风电场主要采用单值确定性的数值预报方法，但现有技术在很多情况下已不能满足电网调度的实际需要。本文提出了一种新的业务风预报的多步预报方法，称为CS-FS-WRF-E模式，它是基于天气研究和预报(WRF)集成预报、新的模糊系统和布谷鸟搜索(CS)算法的次日96步预报方法。首先，利用0.5°水平网格间距全球预报系统(GFS)模式的输出，构造了考虑3个水平分辨率和4个初始场的WRF集合作为基本预报结果。然后，在隶属度的概念下，建立了一种新的模糊系统，该系统能够提取这些集成的特征。在CS优化的帮助下，利用该进化算法对根据物理定律得到的结果进行调整和修正，构建最终的模型，得到最好的预测性能，并优于单个集成成员和所有其他模型进行比较。
Accurate wind speed forecasting, which strongly influences the safe usage of wind resources, is still a critical issue and a huge challenge. At present, the single-valued deterministic NWP forecast is primarily adopted by wind farms; however, recent techniques cannot meet the actual needs of grid dispatch in many cases. This paper contributes to a new multi-step forecasting method for operational wind forecast, 96-steps of the next day, termed the CS-FS-WRF-E model, which is based on a Weather Research and Forecasting (WRF) ensemble forecast, a novel Fuzzy System, and a Cuckoo Search (CS) algorithm. First, the WRF ensemble, which considers three horizontal resolutions and four initial fields, using a 0.5° horizontal grid-spacing Global Forecast System (GFS) model output, is constructed as the basic forecasting results. Then, a novel fuzzy system, which can extract the features of these ensembles, is built under the concept of membership degrees. With the help of CS optimization, the final model is constructed using this evolutionary algorithm to adjust and correct the results obtained based on physical laws, yielding the best forecasting performance and outperforming individual ensemble members and all of the other models for comparison.