RAMP

stochastic simulation of user-driven energy demand time series

authored by

Francesco Lombardi, Pierre-François Duc, Mohammad Amin Tahavori, Claudia Sanchez-Solis, Sarah Eckhoff, Maria C. G. Hart, Francesco Davide Sanvito, Gregory Ireland, Sergio Balderrama, Johann Kraft, Gokarna Dhungel, Sylvain Quoilin

Abstract

The urgency of the energy transition is leading to a rapid evolution of energy system design worldwide. In areas with widespread energy infrastructure, existing electricity, heat and mobility networks are being re-designed for carbon neutrality and are increasingly interconnected. In areas where energy infrastructure is limited, instead, networks and systems are being rapidly
expanded to ensure access to energy for all. In both cases, re-designing and expanding energy systems in these directions requires information on future user behaviour and associated energy demand, yet this type of data is often unavailable. In fact, historical data are often either entirely missing or poorly representative of future behaviour within transitioning systems. This results in reliance on inadequate demand data, which affects system design and its resilience to rapid behaviour evolution.

Organisation(s)

Institute of Computer Science for Business Administration

External Organisation(s)

Delft University of Technology
Reiner Lemoine Institut gGmbH
Vlaamse Instelling voor Technologisch Onderzoek N.V. (VITO)
University of Liege
University of San Simón (UMSS)
University of Cape Town (UCT)
Nordhausen University of Applied Sciences

Type

Article

Journal

J. Open Source Softw.

Volume

9

Pages

6418

No. of pages

4

Publication date

12.06.2024

Publication status

Published

Peer reviewed

Yes

Sustainable Development Goals

SDG 7 - Affordable and Clean Energy

Electronic version(s)

https://doi.org/10.21105/JOSS.06418 (Access: Open)