We helped VirtualMech enhance the efficiency of maintenance for solar farms in Spain. Through intricate AI labeling of drone-captured imagery, the process of identifying damaged, dirty solar parabolic mirrors and distinguishing between healthy and broken heat collector elements was significantly optimized. Overall results include reducing the time taken to detect damages by 70%, cutting down operational costs by €2M, and increasing energy output by 3%.
Image Annotation
Managed Workforce
reduction in time taken to detect damages
in operational cost savings
increase in energy output
In the rapidly evolving field of renewable energy, maintaining efficient solar farm operations presents unique challenges. These challenges include panel maintenance and damage detection, and dealing with adverse impacts of weather and environment, among others. Efficiently diagnosing and managing solar parabolic mirror damage is critical for maintaining constant levels of energy output and reducing maintenance costs. The traditional approach of manual inspections is time-consuming, resource-intensive, and prone to errors and misses. By leveraging AI, solar farm operators can significantly enhance the reliability of their maintenance processes, ultimately leading to higher energy production and lower operational costs.
A 2009 established tech company, VirtualMech specializes in providing Research & Development and Innovative engineering in the Concentrated Solar Thermal industry. It also tracks maintenance and monitoring systems for the Concentrated Solar Power plants.
The client previously relied on manual inspections of solar parabolic mirrors conducted by personnel navigating vast solar farms to check for panel damages. Routine inspections involved technicians driving through each and every row of the solar farm to eye broken panels and Heat collector Equipment (HCEs). This method proved time-intensive and expensive, often resulting in delayed responses to damage, impacting overall energy output.
The client adopted drone surveillance to capture images of solar parabolic mirrors and identify damages. This helped reduce the need to drive down the solar farm to analyze the panels. However, manual effort was still required to go through each image captured by the drone and identify damages to the solar mirrors and HCEs.
Solar Parabolic Mirrors use a parabolic shape to concentrate large areas of sunlight onto a small focal line, significantly increasing the intensity of the solar energy. These mirrors often have tracking systems that allow them to follow the sun’s path across the sky, maximizing the amount of captured solar energy throughout the day.
Heat Collector Equipment (HCEs) are tubes filled with a heat-transfer fluid (HTF), such as synthetic oil or water, which absorbs the concentrated solar energy and heats up. Tubes are placed in the focal line where the sunlight is concentrated from the Solar Parabolic Mirrors. The heated fluid inside HCEs is then transported to a heat exchanger, where the thermal energy from the HTF is transferred to water, producing steam. The generated steam drives a turbine connected to an electrical generator, converting thermal energy into electrical energy.
Initial discussions revealed that the client sought to leverage their existing drone surveillance capabilities more effectively to streamline operations. The client’s objective was to integrate artificial intelligence to minimize human intervention and expedite maintenance responses while reducing errors.
We offered to enhance the client’s current drone surveillance system by providing high-quality image annotation services. Our solution involved annotating the aerial images captured by the drones to accurately detect and categorize damage on solar parabolic mirrors and to distinguish between healthy and broken HCEs.
The core steps in the implementation included:
The adoption of our data annotation services brought about considerable improvements:
The transition to using expertly annotated drone imagery for damage monitoring represents a paradigm shift in managing solar farm operations. It not only streamlined the damage monitoring process but also demonstrated the potential of using professional annotation services in enhancing renewable energy management. The successful implementation serves as a model for similar facilities worldwide seeking to leverage technology for improved efficiency.
Contact us to discover how our data annotation solutions can transform your surveillance systems into highly efficient maintenance tools, maximizing both performance and profitability.
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