PROOF : Predictions of Renewables Optimized for Offshore using Forecasting

This project is supported by Energy Transition Fund (FOD Economie).

Description & objectives

The PROOF project’s objective is the optimization of the offshore maintenance planning requiring outages to:

The project aims at establishing a common methodology that supports the planning of flexible and non-flexible maintenance works, using a weather informed algorithm to optimize maintenance planning according to various constraints like grid constraints and platform accessibility.

PROOF aims at developing an effective approach to offshore substation maintenance planning that fully integrates stakeholders’ interests, while assessing multiple variables, such as weather-related variables and accessibility conditions. In particular, our approach aims to significantly improve the planning by: 

  1. Coordinating stakeholders' criteria in offshore substation maintenance planning.  
  2. Effectively predicting the relevant uncertain variables (e.g. weather evolution) that play a critical role in regulatory, economic, technical and safety factors. 

Notably, aligning stakeholders' criteria in a holistic maintenance planning problem not only reduces the implicit cost of maintenance but also leads to the smooth operation of power systems during maintenance activities. 
On top of that we plan to publish a scientific paper for community knowledge sharing.


Consortium & stakeholders

The consortium is made out of 3 partners :

  • Elia : Consortium leader and business owner
  • N-Side : Development & Industrialization leader
  • UMons : Research & Innovation leader

On top of the consortium partners, the 4 belgian offshore windfarms will also have a role to play in the project as advisory board members to provide the necessary inputs and challenge the projects outcomes.

 

Calendar

Here are the key dates and deliverables :


Funding

This project is supported by Energy Transition Fund (FOD Economie).


Contact

Giovanni Ninite
Maxime Hanot
François Vallée
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