An intelligent control system for large scale commercial solar panel arrays boosts output by turning panels towards the brightest areas of sky.
TrueCapture technology continuously refines the tracking algorithm of each individual solar array in response to weather. The system can deliver 2-6 per cent energy gains to solar panel plants.
Launched by NEXTracker, a Flex company, TrueCapture enables system owners to maximise performance and cut costs for solar facilities.
Solar power plants suffer energy losses from construction variability, terrain undulation and weather. TrueCapture is the first tracker solution to simultaneously solve these factors.
Self-learning system manipulates individual array rows
TrueCapture uses forecast-based tracking behavior algorithms for clouds, fog or haze. Row-to-row (R2R) hybrid closed-loop self-learning corrects the panel direction to minimise loss due to shading.
The system uses self-powered controllers on the tracker to sync with the smart panels and the NEXTracker system. These are connected through Flex’s IoT platform, a secure, NERC-CIP compliant intelligence platform.
From the Flex IoT platform, communication is continually dispatched to control independent solar array rows.
“TrueCapture is our biggest innovation since we introduced independent row, self-powered tracking,” said Dan Shugar, CEO at NEXTracker.
“For the first time, advanced machine learning is being applied to unlock the true potential of power plant performance,” he said.
“We are taking a technology that has been around for over two decades and infusing it with intelligence to meet the needs of a new data-driven world.”
TrueCapture improves on backtracking technique
Backtracking was first introduced in 1991. It uses a microprocessor-based controller which commands the solar PV array to move (‘backtrack’) so no inter-array beam shading occurs.
Backtracking offered a significant improvement in solar panel arrays’ yield. However, TrueCapture advances these gains by incorporating individual row tracking for real world conditions. These include hilly terrain and partly cloudy or fully diffuse conditions.
Furthermore, TrueCapture, proprietary smart panel sensors provide real-time shading information on each tracker row.
The data is processed by machine-learning software to build a virtual 3D model of the job site. An intelligent control engine combines this model with meteorological forecast data and sends optimised tracking commands to every independent row. As a result, energy production gets a significant boost.