Monitoring System for Predictive Energy Management and Maintenance of PV Systems

Existing techniques rely on conventional techniques, which are insufficient and do not ensure increased and optimal utilization of freely available PV energy. We propose predictive energy management and preventive maintenance through monitoring system for PV systems, taking futuristic PV potential and weather forecasts into account in association with the operational parameters of the PV system. This system will optimize operations of off, on, and mix grid operations with higher proportions of PV energy. In addition, maintenance will be predicted to minimize unplanned downtimes of the PV system. Suitable off-the-shelf components will be used for the system with the proposed algorithm to deliver cost effective solution. The proposed research will minimize operational cost, enable efficient distribution and utilization of energy, and reduce greenhouse gas emission. The results of this research will potentially facilitate cost effective integration of PV systems. Concept can easily be extended to other RE and other technologies such as lighting and retrofitting.

Faculty Supervisor:

Kaamran Raahemifar

Student:

Irtaza Syed

Partner:

Green Management Group Inc.

Discipline:

Engineering - computer / electrical

Sector:

Alternative energy

University:

Ryerson University