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

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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.