Cloud-Based Platform for Photovoltaic Assets Diagnosis and Maintenance

Abstract

A cloud-based platform for reducing photovoltaic (PV) operation and maintenance (O&M) costs and improving lifetime performance is proposed in this paper. The platform incorporates a decision support system (DSS) engine and data-driven functionalities for data cleansing, PV system modeling, early fault diagnosis and provision of O&M recommendations. It can ensure optimum performance by monitoring in real time the operating state of PV assets, detecting faults at early stages and suggesting field mitigation actions based on energy loss analysis and incidents criticality evaluation. The developed platform was benchmarked using historical data from a test PV power plant installed in the Mediterranean region. The obtained results showed the effectiveness of the incorporated functionalities for data cleansing and system modeling as well as the platform’s capability for automated PV asset diagnosis and maintenance by providing recommendations for resolving the detected underperformance issues. Based on the DSS recommendations, approximately 7% of lost energy production could be recovered by performing field mitigation activities (e.g., corrective actions).

Keywords

• data cleansing
• decision support system
• energy loss breakdown
• fault detection
• operation and maintenance
• performance monitoring