LEVERAGING AI TO IMPROVE OUR ASSET PERFORMANCE

Monitoring and understanding plant performance can be an extremely difficult task, often requiring our on-the-ground teams to physically inspect equipment and validate assumptions made by remote operators analysing dashboards. This is often due to a lack of remote sensing capabilities with a connected view into performance data. Several of our assets rely on solar trackers to rotate our panels to match the direction of the sun and maximise production levels. Misaligned or vertically stuck trackers can lead to downtimes, underperformance or severe damage and revenue losses if left unattended for too long.

By using Palantir software to connect sensor and SCADA feeds together with satellite imagery processed by Computer Vision models, we have created an app that allows us to remotely identify tracker malfunction in real time and respond to solar trackers in need of maintenance.

With a digital representation of the assets, as well as various data streams (e.g. weather patterns, energy markets and existing maintenance), our team can also drill down into site-specific detection details and take action directly from the platform. Actions are then captured and written back in the app, thus fuelling continuous learning over time.