Welcome to the century of digitalised and decentralised energy systems

Javier Valiño

Head of Energy, Climate and Decabornization Unit
Javier Valiño pic

Our mission is contributing to the evolution, digitalisation, decentralisation and decarbonisation of the Energy Sector. This is done through an asset-driven approach, boosting a more efficient, open, inclusive, innovative and data-driven environment, and combining the most appropriate tools, platforms, and methodologies. This digitalisation beyond the expertise of traditional energy actors requires a trusted ICT provider driving the adoption of emerging and well-adopted ICT technologies, including IoT, Blockchain, AI, among other state-of-the-art technologies. This inclusion also demands adequate business cases to drive this innovation into a traditional sector.


The evolution of the Energy sector demands the coexistence of emerging and legacy solutions, standards for communication at device level, and preparation of the data to be analysed. Platforms should be designed to fit into the reality of the energy sector and be prepared for addressing challenges. In addition, the use of AI is essential to improve the forecasting, optimal scheduling, predictive maintenance, and automation of the sector.

To foster collaboration among different energy vectors such as power, gas, and heat, the FUSE Shuttle (Framework for Utilities and Services) has been developed with the aim to reduce integration problems, keep under control data sharing and interaction, and provide added value through advanced services using valorised data.


FUSE platform is the sector key asset. It is based on open standards/APIs to support interoperability, modularity, scalability, and, therefore, pave the way towards an inclusive energy ecosystem. Main challenges are:

  • Management of data heterogeneity and its preparation for service development.
  • Sustainable integration of Electric Vehicles (EVs) in cities and management of energy flows for charging.
  • Management of Distributed energy resources to optimise grid operation and maintenance.
  • Customer segmentation based on consumption patterns.
  • Cross-energy vector collaboration to maximise renewable generation capacity, promote self-consumption, and reduce the dependence on fossil fuels.
  • Provision of reliable Modelling and Forecasting mechanisms enabling efficient planning of energy assets.
  • Development of flexibility scheduling mechanisms to maximise the revenue and optimise the behavior of energy stakeholders.
  • Includion of predictive maintenance and digital twin modelling techniques so as to enlarge the operational life of energy assets.

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