ΑΙhub.org
 

AI as an accelerator of the energy transition, opportunities for a carbon-free energy system

by
23 September 2021



share this:
NL AI coalition report front cover

In the next ten years, the Netherlands aim to take major steps towards increasing the amount of renewable energy produced and the electrification of heat demand and mobility. This desire requires a complete and highly complex transformation of the energy system. The fossil, central energy system is changing into a decentralised system based on renewable energy. Algorithms and AI can make a significant difference in accelerating this transition and in achieving an efficient and sustainable energy system.

When making decisions about the energy transition, such as investing in infrastructure or placing renewable sources, much depends on predictions, often based on limited data, and there are many different interests. New AI techniques can support these kinds of investment and design questions in order to better base them on facts, take better account of multiple interests, and also better explain the choices made and related uncertainties. In addition, there are opportunities for AI in automating energy system operations, supporting energy services, and predicting and automating maintenance. The opportunities and challenges for AI in this context were mapped out in a position paper, AI as an accelerator of the energy transition, opportunities for a carbon-free energy system. This document provides a guideline for next steps in research and innovation, and can serve as a framework of reference for opportunities and challenges that we cannot yet foresee.

This paper is written on behalf of the working group on Energy and Sustainability from the Netherlands AI Coalition (NL AIC). The aim of this working group is to support the development of new AI solutions for challenges in the energy sector and around sustainability and thereby stimulate the Dutch economy. This is achieved by bringing together expertise in AI and from the relevant sectors, and by supporting new collaborations to tackle these types of challenges. Please visit this page for more information.

Reference

The position paper AI as an accelerator of the energy transition, opportunities for a carbon-free energy system is written by Pallas Agterberg, Maarten Bijl, Johann Hurink, Han La Poutré, Gerdien van de Vreede, Mathijs de Weerdt and Tijs Wilbrink on behalf of the working group Energy and Sustainability of the NL AIC.

AIhub focus issue on affordable and clean energy

tags: ,


Mathijs de Weerdt is Associate Professor on Algorithms for Planning and Optimization at Delft University of Technology.
Mathijs de Weerdt is Associate Professor on Algorithms for Planning and Optimization at Delft University of Technology.




            AIhub is supported by:


Related posts :



Are emergent abilities of large language models a mirage? – Interview with Brando Miranda

We hear about work that won a NeurIPS 2023 outstanding paper award.
25 April 2024, by

We built an AI tool to help set priorities for conservation in Madagascar: what we found

Daniele Silvestro has developed a tool that can help identify conservation and restoration priorities.
24 April 2024, by

Interview with Mike Lee: Communicating AI decision-making through demonstrations

We hear from AAAI/SIGAI Doctoral Consortium participant Mike Lee about his research on explainable AI.
23 April 2024, by

Machine learning viability modelling of vertical-axis wind turbines

Researchers have used a genetic learning algorithm to identify optimal pitch profiles for the turbine blades.
22 April 2024, by

The Machine Ethics podcast: What is AI? Volume 3

This is a bonus episode looking back over answers to our question: What is AI?
19 April 2024, by

DataLike: Interview with Tẹjúmádé Àfọ̀njá

"I place an emphasis on wellness and meticulously plan my schedule to ensure I can make meaningful contributions to what's important to me."




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association