山东电力高等专科学校学报

为应对新能源发电规模扩大带来的数据处理难题，提升新能源电站的运行与管理水平，在Hadoop大数据框架下，设计开发了具有数据采集、存储、分析及预测功能的新能源发电数字化集中监视系统。该系统通过物联网、大数据、人工智能及云计算技术，采用分层架构实现多源数据融合，进行发电功率预测。在应用实践中，监视系统完整地记录了发电系统数据，并准确预测了未来的发电功率，验证了其数据处理与分析的准确性和可靠性。

To cope with the data processing problems brought about by the expansion of new energy power generation scale,and to improve the operation and management level of new energy power plants,a digitalized centralized monitoring system for new energy power generation featuring data collection,storage,analysis and prediction has been designed and developed under the Hadoop big data framework.By using internet of things(IoT),big data,artificial intelligence(AI)and cloud computing technologies,the system adopts a layered architecture to realize multi-source data fusion for power prediction.During the application practice,the system has completely recorded the data of the power generation system and accurately predicted the future power,which verifies the accuracy and reliability of its data processing and analysis.