Optimal scheduling of a multi-energy hub with integrated demand response programs
Zubo, Rana H.A. Onen, Patrick S.
Zubo, Rana H.A.
Onen, Patrick S.
Publication Date
2025-09
End of Embargo
Supervisor
Rights
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Peer-Reviewed
Yes
Open Access status
openAccess
Accepted for publication
2025-09-04
Institution
Department
Awarded
Embargo end date
Additional title
Abstract
This paper presents an optimal scheduling framework for a multi-energy hub (EH) that integrates electricity, natural gas, wind energy, energy storage systems, and demand re-sponse (DR) programs. The EH incorporates key system components including transform-ers, converters, boilers, combined heat and power (CHP) units, and both thermal and elec-trical energy storage. A novel aspect of this work is the joint coordination of multi-carrier energy flows with DR flexibility, enabling consumers to actively shift or reduce loads in response to pricing signals while leveraging storage and renewable resources. The opti-misation problem is formulated as a mixed-integer linear programming (MILP) model and solved using the CPLEX solver in GAMS. To evaluate system performance, five case stud-ies are investigated under varying natural gas price conditions and hub configurations, including scenarios with and without DR and CHP. Results demonstrate that DR partici-pation significantly reduces total operating costs (up to 6%), enhances renewable utilisa-tion, and decreases peak demand (by around 6%), leading to a flatter demand curve and improved system reliability. The findings highlight the potential of integrated EHs with DR as a cost-effective and flexible solution for future low-carbon energy systems. Further-more, the study provides insights into practical deployment challenges, including storage efficiency, communication infrastructure, and real-time scheduling requirements, paving the way for hardware-in-the-loop and pilot-scale validations.
Version
Published version
Citation
Zubo RHA, Onen PS, Mujtaba IM et al (2025) Optimal scheduling of a multi-energy hub with integrated demand response programs. Processes. 13(9): 2879.
Link to publisher’s version
Link to published version
Link to Version of Record
Type
Article