DeP2WIND: A data-driven framework for the sustainable reuse of decommissioned petroleum platforms as support structures for wind energy production is a project aimed at accelerating the energy transition and repurposing existing steel waste in the marine environment. Offshore platforms in marine environments have long been researched and used for oil and gas exploration, with a significant impact on the European energy sector. Nonetheless, these constructions are abandoned in the sea after their operating lifespan and are not fully decommissioned, posing a pollution danger to the surrounding environment.
The DeP2WIND project proposes new frameworks for managing the reuse and repurposing of such structures based on their health state. The project investigates multidisciplinary techniques to analyzing the status of decommissioned platforms and addressing corrosion behavior in steel components. These innovative technologies will serve as the foundation for deciding how to reuse or recycle these structures.
Motivation and Problems addressed:
Approximately 6,000 offshore oil and gas platforms are in operation around the world, with 2,500 to 3,000 offshore petroleum platforms - or nearly half - expected to be decommissioned over the next 17 years because they will no longer be economically viable to operate. This will result in massive steel trash in the marine environment, which must be handled.
The DeP2WIND project tackled a variety of engineering problems, beginning with simulating the degradation state of the steel platform due to corrosion caused by the harsh climate, as well as evaluating the structure's reliability over time and which parts should be maintained or replaced. Furthermore, the project addresses the issue of new wind turbine designs that will be mounted on the resulting platform in the future.
Pathway to impact:
The successful completion of the DeP2WIND project has positioned its output as transformative tools for accelerating energy transition in a safe path, by minimizing steel waste and repurposing steel elements in a cost-effective way to boost renewable energy. By providing more accurate models for predicting steel deterioration in marine environments, a cost-effective maintenance-based reliability approach may be simply adopted to minimize maintenance costs while increasing structural safety. Furthermore, the employment of optimization theory-based AI assists in implementing novel designs of wind turbines.
