Electrical Signal Data Mining for Diagnosis, Monitoring, and Prediction in Wind and Solar Power Plants.

在风能和太阳能发电计划中用于诊断、监测和预测的电信号数据挖掘加拿大电网中以可再生能源为基础的发电厂的利用率已大大提高。在不同的可再生能源技术中，风能和太阳能所占份额最高。降低运行维护(O&M)成本是近十年来研究的重点。Arista Renewable Energy拥有一个庞大的数据库，通过1赫兹频率的监控和数据采集(SCADA)收集不同发电厂的信息。这些数据将用于开发适当的电气状态监测(CM)工具。然后，将所开发的工具与Arista开发的进行机械CM的软件DIGNOSTIX Tool合并。结果将是一个全面的CM工具，包括电气和机械两个方面。计算机科学和数据挖掘的概念将被用来从手动CM转向智能CM。开发的SMART CM将能够解释收集到的数据，诊断系统现有的故障或性能不佳，并预测未来的故障，从而显著降低运营和维护成本，帮助阿里斯塔保持其竞争优势，并提高加拿大风能和太阳能发电厂的效率。

ELECTRICAL SIGNAL DATA MINING FOR DIAGNOSIS, MONITORING, AND PREDICTION IN WIND AND SOLAR POWER PLANTSUtilization of renewable energy-based power plants has been considerably augmented in Canada's power network. Among different renewable energy technologies, wind and solar energies have the highest share. Reduction of operation and maintenance (O&M) costs has been the focal point of research in the recent decade. Arista Renewable Energies has a vast database of different power plants gathered by Supervisory Control And Data Acquisition (SCADA) at 1 Hz frequency. These data will be used to develop a proper Electrical Condition Monitoring (CM) tool. Afterwards, the developed tool will be merged with DIGNOSTIX tool, which is a software developed by Arista to conduct Mechanical CM. The result will be a comprehensive CM tool which includes both Electrical and Mechanical aspects. The computer science and data mining concepts will be utilized to move from a manual CM toward a smart CM. The developed smart CM will be able to interpret gathered data and diagnose existing faults or underperformance of system and also, predict future failures which can decrease O&M costs noticeably and help Arista to maintain its competitive-edge and increase efficiency of wind and solar power plants in Canada.