Drone Solar Panel Inspection: A Case Study on PCL Construction
Technology Category
- Drones - Drone Payloads & Accessories
- Drones - Multirotor Drones
Applicable Industries
- Cement
- Renewable Energy
Applicable Functions
- Maintenance
- Quality Assurance
Use Cases
- Agricultural Drones
- Computer Vision
Services
- Drone Operation Services
- Testing & Certification
The Customer
PCL Construction
About The Customer
PCL Construction is the largest construction company in Canada and one of the largest in the United States. The company has built its reputation on the simple premise of building success for its clients. PCL Construction takes on projects of varying sizes and scopes, bringing to life the goals of their customers through an innovative approach. Drone data has become integral to their operations, especially for solar construction projects. These projects range in size from small to massive, and once construction gets underway on the larger fields, it happens at a breakneck speed, making drone data all the more valuable.
The Challenge
PCL Construction, one of the largest construction companies in Canada and the United States, faced a significant challenge when it came to drone data capture for solar construction projects. The company's existing quadcopters and multirotors were not sufficient for the task due to the repetitive and demanding nature of solar field construction projects. These projects required reliable data for daily monitoring, which the existing drones could not provide. The construction of solar fields happens in 'waves,' with production teams driving more than a thousand piles a day and module crews placing five times as many solar panels in the same timeframe. This fast-paced, large-scale construction offered a limited view from the ground, making drone data crucial. However, the company needed a dependable workflow and a processing engine that could deliver orthomosaics to the superintendent every night.
The Solution
To address this challenge, PCL Construction upgraded their drone technology from the 20 MP Sony QX1 payload to the RX1R II. The company flies two GEN I WingtraOne drones, which provide a 'snapshot in time' of the construction progress. This allows the team to see how things are progressing with a historical series of images, making the project more efficient. The drones capture a moment in time, rather than a puzzle of moments under varying lighting and weather conditions. The team uses the data for different solar project inspection objectives, including volume calculations, progress tracking, and surface comparisons. To do this most efficiently, PCL partnered with AI Clearing, a technology company that rapidly incorporates design and drone data into project insights through visually rich dashboards. The WingtraOne drones have proven to be a more efficient solution, capable of capturing the same amount of data in one hour that would take an entire day with a large multirotor.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Vestas: Turning Climate into Capital with Big Data
Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.
Case Study
Siemens Wind Power
Wind provides clean, renewable energy. The core concept is simple: wind turbines spin blades to generate power. However, today's systems are anything but simple. Modern wind turbines have blades that sweep a 120 meter circle, cost more than 1 million dollars and generate multiple megawatts of power. Each turbine may include up to 1,000 sensors and actuators – integrating strain gages, bearing monitors and power conditioning technology. The turbine can control blade speed and power generation by altering the blade pitch and power extraction. Controlling the turbine is a sophisticated job requiring many cooperating processors closing high-speed loops and implementing intelligent monitoring and optimization algorithms. But the real challenge is integrating these turbines so that they work together. A wind farm may include hundreds of turbines. They are often installed in difficult-to-access locations at sea. The farm must implement a fundamentally and truly distributed control system. Like all power systems, the goal of the farm is to match generation to load. A farm with hundreds of turbines must optimize that load by balancing the loading and generation across a wide geography. Wind, of course, is dynamic. Almost every picture of a wind farm shows a calm sea and a setting sun. But things get challenging when a storm goes through the wind farm. In a storm, the control system must decide how to take energy out of gusts to generate constant power. It must intelligently balance load across many turbines. And a critical consideration is the loading and potential damage to a half-billion-dollar installed asset. This is no environment for a slow or undependable control system. Reliability and performance are crucial.
