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Academy for Energy Transition

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Skills for future

Academy for Energy Transition

Monday 24, July 2023
Skills for future
Skills for future
In Portugal, discussing the energy transition.

EDP held, with Jornal de Negócios, a series of conferences, with the participation of universities, to discuss the energy transition.

Dialogue with the Academy

EDP, in partnership with Jornal de Negócios, held a cycle of conferences with leading universities to discuss the contribution of electricity distribution networks to the energy transition in 2022. The first conference took place at the Faculty of Engineering of the University of Porto, on June 6, 2022.

Digitalization and the construction of a progressively smarter electricity grid has been assumed as one of the strategic pillars of the response to the challenges and to obtain benefits from the energy transition. 

In this context, the projects that EDP, through E-REDES, has been developing over the last few years have had a strong focus on research and development in areas related to the evolution of the electricity distribution system, almost always based on the new possibilities created by the emergence and massification of smart grids and their ramifications.

In recent years, the number of initiatives resulting from the collaboration between EDP and entities in the scientific and technological sector has multiplied. For example:

  • Development of new network planning tools, adapted to the changes imposed by the introduction of distributed energy resources such as renewable generation or electric vehicle charging systems.
  • Development of new IoT (Internet of Things) and advanced analytics tools and technologies, which allow the management of technical assets in distribution networks in a more efficient way and from a risk-controlled perspective.
  • Initiatives that have enabled the emergence of new means of inspecting distribution networks, using satellite images, drones or thermographic cameras to improve the inspection of overhead lines or advanced supervision methods for power transformers. They make it possible to anticipate faults in their operation, from a predictive maintenance perspective.

 

Main Classifications
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Impact

13
Direct beneficiaries
12
Employees volunteering
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