Risk-aware resistance enhancement for integrated heat and power supply driven by physics-informed meteorological data
Lan, Xinyao ; Jiang, Haiyang ; Jiang, Xiaoman ; Andersson, Martin LU
; Strbac, Goran
; Qi, Ning
; Fang, Yuchen
; Du, Ershun
and Zhang, Ning
(2026)
In Applied Energy
424.
- Abstract
Cold extremes bring significant uncertainties to the energy system. Their strong spatiotemporal coupling introduces growing challenges to the adequacy and flexibility of the power and heating supply, complicating risk identification and mitigation. Therefore, this paper presents a framework for spatiotemporal risk assessment and resistance enhancement under cold extremes. It captures cold-air propagation using a trajectory-informed method and quantifies the inadequacy of the heating supply through multiple risk indicators. Based on this, a risk-aware scheduling strategy is developed to improve the coordination of power and heating supply and enhance system resistance during cold extremes. Empirical studies on the biomass-based combined... (More)
Cold extremes bring significant uncertainties to the energy system. Their strong spatiotemporal coupling introduces growing challenges to the adequacy and flexibility of the power and heating supply, complicating risk identification and mitigation. Therefore, this paper presents a framework for spatiotemporal risk assessment and resistance enhancement under cold extremes. It captures cold-air propagation using a trajectory-informed method and quantifies the inadequacy of the heating supply through multiple risk indicators. Based on this, a risk-aware scheduling strategy is developed to improve the coordination of power and heating supply and enhance system resistance during cold extremes. Empirical studies on the biomass-based combined heat and power supply in Sweden demonstrate the effectiveness of the proposed approach in reducing heating supply inadequacy and external energy dependence.
(Less)
- author
- Lan, Xinyao
; Jiang, Haiyang
; Jiang, Xiaoman
; Andersson, Martin
LU
; Strbac, Goran
; Qi, Ning
; Fang, Yuchen
; Du, Ershun
and Zhang, Ning
- publishing date
- 2026-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Climate resistance, Cold extremes, Integrated heat and power, Meteorological data-driven, Physics-informed modeling
- in
- Applied Energy
- volume
- 424
- article number
- 128469
- pages
- 12 pages
- publisher
- Elsevier
- external identifiers
-
- scopus:105045171907
- ISSN
- 0306-2619
- DOI
- 10.1016/j.apenergy.2026.128469
- language
- English
- LU publication?
- no
- id
- 020a7595-b629-43cf-a3b2-fb9319b6fd6d
- date added to LUP
- 2026-07-30 19:15:44
- date last changed
- 2026-08-31 15:57:19
@article{020a7595-b629-43cf-a3b2-fb9319b6fd6d,
abstract = {{<p>Cold extremes bring significant uncertainties to the energy system. Their strong spatiotemporal coupling introduces growing challenges to the adequacy and flexibility of the power and heating supply, complicating risk identification and mitigation. Therefore, this paper presents a framework for spatiotemporal risk assessment and resistance enhancement under cold extremes. It captures cold-air propagation using a trajectory-informed method and quantifies the inadequacy of the heating supply through multiple risk indicators. Based on this, a risk-aware scheduling strategy is developed to improve the coordination of power and heating supply and enhance system resistance during cold extremes. Empirical studies on the biomass-based combined heat and power supply in Sweden demonstrate the effectiveness of the proposed approach in reducing heating supply inadequacy and external energy dependence.</p>}},
author = {{Lan, Xinyao and Jiang, Haiyang and Jiang, Xiaoman and Andersson, Martin and Strbac, Goran and Qi, Ning and Fang, Yuchen and Du, Ershun and Zhang, Ning}},
issn = {{0306-2619}},
keywords = {{Climate resistance; Cold extremes; Integrated heat and power; Meteorological data-driven; Physics-informed modeling}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Applied Energy}},
title = {{Risk-aware resistance enhancement for integrated heat and power supply driven by physics-informed meteorological data}},
url = {{http://dx.doi.org/10.1016/j.apenergy.2026.128469}},
doi = {{10.1016/j.apenergy.2026.128469}},
volume = {{424}},
year = {{2026}},
}