As the transition of the energy system rely on reducing the overall energy demand and making the energy supply side climate neutral, their control systems need to help making the energy supply side cleaner, more secure, and competitive by boosting cost performance and reliability of a broad portfolio of renewable energy solutions, in line with societal needs and preferences. So far, most wind farm installations, on shore or off shore, work unattended in remote areas, without any integrated system monitoring their physical security, performance or other operational issues that may affect their overall output.

The proposal is expected to develop new or enhance existing solutions for integrated systems, for wind farm (land and shore) management that will:

• Develop open-source data-driven tools to decrease energy costs on operation, while increasing total wind farm output
• Develop of digital and physical tools, as well as interoperable frameworks and controls, for enhanced data collection, analysis, and operation aimed.
• Allow operators to make better informed decisions on farm-wide system optimization, lifetime extension, decommissioning and/or recycling of components.
• Contribute to LCOE reduction in line with the SET Plan targets

New data collection and analysis, and applications towards the development monitoring systems either from ground sensors and/or earth observations on a decentralized way is the core of the solution. The goal is to collect actionable (cross-border) evidence data acceptable by policy makers and wind farm operators with the ultimate goal to respond promptly and with full capacity following the most transparent workflows and methods in decision under a unique risk management methodology.

Through the project we will create a blockchain based database platform that contains all related data, such as daily power production from each wind turbine as well as their energy consumption using devices equipped with IoT spart tagging.

The proposal is expected to address all the following aspects:

• Address and validate digital innovation on wind farm control techniques able to provide more stable, resilient, secure, reliable and affordable energy, while retaining high levels of cybersecurity. Focus on farm output maximization is expected.
• Concluded with systems and work procedures allowing these data-driven innovations to reduce operational and maintenance costs, to increase energy output, and their impact on (component, turbine, farm) lifetime.
• Address the role of such innovations as a prognostic tool, regarding failures and damages:
• Develop and release an open source digital/AI solution for sector uptake. This tool is expected to be built from concrete experiments and data measurements