As utility-scale solar matures, investors and asset owners are looking beyond installed capacity towards operational performance, resilience and long-term yield. This is changing expectations for PV tracker systems, particularly as projects move onto more difficult terrain and face increasingly variable weather.
Jörg Scholz, Managing Director at Gantner, argues that tracker control is evolving from a positioning mechanism into an intelligent, data-driven part of PV infrastructure.
Moving beyond astronomical models
Conventional trackers typically use solar position algorithms based on time, date and geographical location. Under predictable conditions, this approach works well, but real plants must also contend with cloud movement, diffuse irradiation, terrain, wind, temperature and humidity.
These variables can affect the optimum tracker angle and overall plant performance.
The economic implications can be significant. Scholz says that across gigawatt-level portfolios, even a 1 to 2 per cent improvement in yield can translate into additional revenue over a 25-year operating life.
Adapting to real conditions
Machine learning-supported control can combine live measurements, historical patterns and forecasts rather than following a fixed daily trajectory.
Gantner says its trackIQ platform considers inputs including:
Tracker angles can then be adjusted according to actual conditions.
Diffuse light is one area of particular interest. Conventional tracking primarily follows direct sunlight, but scattered light can account for a substantial proportion of generation under variable weather. Optimising module orientation for both can potentially increase production without adding generation hardware.
Large solar installations illustrate the operational challenge. Thousands of tracker rows must respond consistently while local conditions can vary across the site.
Managing difficult terrain
Suitable flat land is becoming harder to secure in many solar markets. This is pushing utility-scale projects towards sloped and irregular sites, where elevation differences between rows can cause shading, mismatch losses and maximum power point tracking (MPPT) inefficiencies.
Adaptive terrain tracking can calculate angles row by row using three-dimensional backtracking based on elevation and CAD data.
According to Gantner, combining this geometry with real-time measurements allows the control strategy to be continually refined. Algorithms can also operate locally onsite, reducing dependence on external connectivity.
Building resilience into control
Tracker systems increasingly have another responsibility: protecting equipment during extreme weather.
Forecast and live data can allow arrays to move automatically into safer positions before high winds, hail, flooding or snow events. This changes tracker control from purely yield optimisation towards a combination of performance and asset protection.
At the same time, greater connectivity creates cybersecurity requirements. The EU NIS2 Directive and Cyber Resilience Act (CRA) are important considerations for connected renewable infrastructure.
Modern control systems may therefore require:
Gantner says trackIQ has been developed with these requirements in mind.
From tracker to digital infrastructure
Tracker control is increasingly connected with commissioning, monitoring, analytics, remote diagnostics and fleet-wide performance management.
Gantner says technologies of this kind are already operating in more than 53 countries. One project in Chile uses more than 6,000 individual tracker control units on a single DC-powered wireless mesh network.
For Scholz, the direction of travel is clear. As PV plants become larger and more interconnected, tracker control must respond to changing weather, terrain, cybersecurity risks and operating conditions rather than simply follow the theoretical position of the sun.
The tracker is therefore becoming less of a standalone mechanical subsystem and more of an intelligent control layer within the modern solar plant.
Read the complete insight from Gantner on intelligent PV tracking, machine learning, terrain optimisation and cybersecurity in PES Solar: https://pes.eu.com/exclusive-articles/the-rise-of-intelligent-pv-tracking