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

用于风能和太阳能发电厂诊断、监测和预测的电信号数据挖掘。

• 批准号: 537810-2019
• 负责人: Chandra, Ambrish
• 金额: $ 1.82万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=680620
• 关键词: Electrical; Signal; Data; Mining; Diagnosis

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.

用于风能和太阳能发电厂诊断、监测和预测的电信号数据挖掘在加拿大的电力网络中，可再生能源发电厂的利用已经大大增加。在各种可再生能源技术中，风能和太阳能所占份额最高。降低运行维护成本是近十年来研究的重点。Arista Renewable Energies拥有由监控和数据采集（SCADA）以1 Hz频率收集的不同发电厂的庞大数据库。这些数据将用于开发适当的电气状态监测（CM）工具。之后，开发的工具将与DIGNOSTIX工具合并，DIGNOSTIX工具是由Arista开发的用于进行机械CM的软件。其结果将是一个全面的CM工具，包括电气和机械方面。计算机科学和数据挖掘的概念将被用来从手动CM走向智能CM。开发的智能CM将能够解释收集的数据并诊断系统的现有故障或性能不佳，还可以预测未来的故障，这可以显着降低O&M成本，帮助Arista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。