Predicting Optimal Temperature in The Transmission System (CTR)

Updated on June 12, 2023
GOTO Aarhus 2023
Maria Jensen
Maria Jensen

Co-Founder and Machine Learning Engineer at neurospace

Centralkommunernes Transmissionsselskab (CTR) has in collaboration with Neurospace explored whether already existing data and Machine Learning can predict the optimal supply temperature, without risking universal service obligations, while optimizing the supply temperature to provide cheaper and greener district heating. Two Machine Learning models are created; one to predict the optimal temperature, and another to estimate whether the predicted supply temperature causes network congestion.

During this presentation, we will discuss the challenge at hand, the significance of working in closely collaboration with domain experts, and the proposed solution.