This case study examines potential systemwide reductions in carbon emissions from the increased use of robotic inspections to prevent boiler tube failures.
A range of innovations have emerged focused on our global transition to a net zero economy. From electric planes to direct air capture, these technologies present promising solutions to our net zero aspirations and can be complemented by solutions that reduce the emissions associated with today's infrastructure. This case study examines the use of robotic inspections in improving the efficiency, resilience, and sustainability performance of today's energy infrastructure.
Natural gas and coal power plants provide the bulk of the global power generated for electrical grids; however, this critical infrastructure is aging, leading to forced outages. These outages threaten plants' ability to reliably produce energy on demand and typically lead to increased CO2 emissions through the use of back-up generation. This study finds that, by decreasing the occurrence of forced outages, robotic inspections and decision-making software may provide several concrete benefits if they were to be rapidly adopted:
- Robotic inspections combined with decision making software have the potential to reduce global CO2 emissions by 52-230 million metric tons (MMT) CO2 annually if they were to be deployed immediately and at a global scale. For comparison, this is equivalent to eliminating between 1.1%-4.8% of annual emissions in the U.S. By identifying corrosion before it leads to unplanned downtime, robotic inspections help power plants reduce their reliance on backup generation.
- Robotic inspections that eliminate boiler tube failures could lead to, on average, 32% lower CO2 emissions per unit of electricity generated by keeping base load generators in service rather than relying on more GHG intensive peaker plants and other forms of backup generation.
- These technologies are commercially available today and could have an immediate impact on the boiler tube failure if deployed at scale.