A hybrid time-and-event-driven strategy for integrated community energy system planning

Qu, Jiawei, Hou, Kai, Liu, Zeyu, Zhou, Yue ORCID: https://orcid.org/0000-0002-6698-4714, Zhu, Lewei, Dong, Xiaohong, Mu, Yunfei and Jia, Hongjie 2025. A hybrid time-and-event-driven strategy for integrated community energy system planning. Applied Energy 384 , 125274. 10.1016/j.apenergy.2025.125274 Item availability restricted.

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Abstract

Unpredictable events such as technological breakthroughs and energy policy shifts can cause significant errors in the forecast of the parameters like equipment performance and energy demands. Traditional single-stage and fixed multi-stage planning methods struggle with unpredictable events, severely impacting the accuracy of the planning of Integrated Community Energy Systems (ICES). As a solution, a Hybrid Time-and-Event-Driven Multi-Stage Planning (HTED-MSP) method is proposed for ICES. The HTED-MSP method determines the start time of each planning stage based on a combination of time and specific event. Specifically, the event-driven strategy mitigates unpredictable changes in load growth, energy prices, and technological advancements on costs, with trigger conditions determined by marginal cost analysis. Meanwhile, the time-driven strategy enhances long-term reliability of ICES. Considering the significant impact of renewable energy variability and equipment failures on reliability, the HTED-MSP method quantifies these factors using 8760-h normal and N-k contingency scenarios. A State Similarity (SS) method is then proposed to address the computational burden of massive scenarios by simplifying the optimization process into an equation-solving approach. The case study demonstrates that HTED-MSP significantly reduces additional costs caused by unpredictable events. The computational efficiency of the SS method is more than ten times greater than the existing two-stage algorithms.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Publisher:	Elsevier
ISSN:	0306-2619
Funders:	National Natural Science Foundation of China program .
Date of First Compliant Deposit:	3 April 2025
Date of Acceptance:	2 January 2025
Last Modified:	04 Apr 2025 15:30
URI:	https://orca.cardiff.ac.uk/id/eprint/177378

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