Browse by author
Lookup NU author(s): Professor Vladimir TerzijaORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/Uncertainties in energy prices and demand during market clearing pose severe operational challenges to integrated energy service providers, exacerbated by complex multi-energy coupling and stringent system constraints. To address these challenges, this paper proposes a multi-objective credibility-based robust optimization method to enhance the risk resilience of integrated energy service providers in electricity–gas coupled markets. Specifically, we develop an uncertainty quantification model based on credibility theory that integrates possibility and necessity measures to systematically characterize multiple risk sources. Furthermore, we establish a fuzzy chance-constrained programming model incorporating multiple trading markets and transform it into a computationally tractable robust optimization framework, effectively overcoming the conservatism of traditional methods while maintaining solution efficiency. In a case study based on an IEEE 33-node distribution system and a 32-node district heating network, the proposed method achieves a credibility level of 0.79 under a risk aversion factor of 0.1, while significantly reducing operational costs compared to traditional robust optimization and distributionally robust optimization approaches. The results demonstrate that this approach can guide integrated energy service providers to dynamically adjust their energy transaction structure, such as increasing fixed-price contracts and reducing spot market exposure, thereby forming a cost-effective and robust trading strategy.
Author(s): Cong X, Terzija V, Xu B, Chen J
Publication type: Article
Publication status: Published
Journal: International Journal of Electrical Power and Energy Systems
Year: 2026
Volume: 176
Print publication date: 01/03/2026
Online publication date: 18/02/2026
Acceptance date: 11/02/2026
Date deposited: 15/04/2026
ISSN (electronic): 1879-3517
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.ijepes.2026.111688
DOI: 10.1016/j.ijepes.2026.111688
Data Access Statement: Data will be made available on request.
Altmetrics provided by Altmetric
