摘要： 我国新能源近年发展迅速，风电已成为了目前主要的发电方式之一。随着大数据、人工智能、物联网、云计算、自然语言处理技术的发展和国家政策的支持，大数据分析在风电智能化领域逐步得到广泛应用。通过对风电数据采集与监视控制(Supervisory Control and Data Acquisition,SCADA)系统重新进行架构设计，搭建了一套基于SCADA的风电数据分析平台，将数据进行归类、采集、传输、预处理、存储。平台将风电数据进行重新定义，从多个维度对设备及系统进行实时评价，同时引入多元状态估计技术验证了平台可以对模型的性能指标有更好的提升。该研究旨在通过大数据分析进行故障预警及操作指导，建立具有新型能源体系的智能管控平台，进而提高风电场的运维效率和可靠性。
Design and implementation of wind power data analysis platform based on SCADA
Wang Xin，Xu Song， Leng Ke
Intelligence Technology of CEC Co., Ltd.
Abstract： In recent years, China′s new energy has developed rapidly, and wind power has become one of the main power generation methods. With the development of big data, artificial intelligence, the Internet of Things, cloud computing, and natural language processing technologies, as well as the support of national policies, big data analysis has gradually been widely applied in the field of wind power intelligence. By redesigning the architecture of the Supervisory Control and Data Acquisition (SCADA) system for wind power, a SCADA-based wind power data analysis platform was built to classify, collect, transmit, preprocess and store the data. The platform redefines wind power data, evaluates equipment and systems in real time from multiple dimensions, and introduces multivariate state estimation technology to verify that the platform can better improve the performance indicators of the model. This research aims to use big data analysis to conduct fault warning and operation guidance, establish an intelligent control platform with a new energy system, and thereby improve the operational efficiency and reliability of wind farms.
Key words : SCADA;wind power; big data; data analysis
