Solar Asset Performance Monitoring & Assessment
Real-time data and intelligence solutions enabling reliable solar PV fleet performance benchmarkingTo optimize O&M budgets and maximize ROI, solar asset managers need to reduce costs and increase efficiency using scalable approaches to solar asset monitoring
Solar plant operators, managers and investors need the ability to evaluate the performance of individual solar PV systems or fleets of PV systems. To make better asset management and O&M decisions, avoid unnecessary lost energy production, and reduce performance risk or unnecessary truck rolls, solar stakeholders carefully research tools and resources for benchmarking PV system performance.
Solar Asset Monitoring
When choosing a solution for on-demand production, irradiance and weather data, solar stakeholders should consider several key factors:
Expertise
Is the solar data produced by an experienced staff of scientists, researchers & engineers with a deep bench of scientific expertise?
When sourcing a solar asset performance and monitoring dataset solution, choose a solution that is supported by a broad team of experienced solar industry experts that incorporates the industry’s leading solar data.
Trust
Does the solar data build investor confidence?
A solar asset and performance monitoring solution should be proven to validate energy projections. It should successfully benchmark solar fleet performance with monthly summaries of expected asset performance based on available irradiance.
Reliability
Does the solar data improve field services & customer support?
Solar stakeholders should embrace solutions that can keep field teams and customers informed by reliably integrating hourly solar performance estimates and weather data.
Scalability
Is the solar data accessible by diagnostic software?
To scale solar asset monitoring, stakeholders should integrate solar data with diagnostic software. With integration, it’s possible to generate expected power output measurements of individual or fleets of PV systems—all at a lower cost and more accurately than using ground measurements.