Enhancing the Resilience of Distributed Energy Storage on Smart Highways: A System Dynamics Approach for Dynamic Maintenance Decision-Making

The resilience of Intelligent Transportation Systems (ITSs) heavily relies on distributed Battery Energy Storage Systems (BESSs) deployed in harsh, unattended highway environments. Traditional maintenance strategies often fail to account for the dynamic feedback between battery aging, environmental stress, and maintenance response latency. This study proposes a system dynamics (SD) framework to evaluate and optimize the resilience of these critical power infrastructures. By modeling the nonlinear interactions among sensor data, controller logic, and remote discharge terminals, we simulate the system’s dynamic behavior over a 36-month lifecycle. The results reveal a critical “scalability threshold”: when battery pack quantity exceeds 40 units, the system’s self-healing time increases disproportionately, degrading resilience. Furthermore, the study identifies 384 V as the optimal “Resilience Topology Voltage”, offering the fastest recovery speed by balancing thermal stability with consistency management efficiency. These findings provide theoretical guidelines for configuring BESS capacity and optimizing remote maintenance protocols to ensure uninterrupted highway operations.

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Publication Details

Journal
Energies
Published
2026-03-03
DOI
https://doi.org/10.3390/en19051259
Primary Topic
Advanced Battery Technologies Research
Type
article
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article

Enhancing the Resilience of Distributed Energy Storage on Smart Highways: A System Dynamics Approach for Dynamic Maintenance Decision-Making

Xiaochun Peng, Yanqun Yang
Energies
Advanced Battery Technologies Research
article

Enhancing the Resilience of Distributed Energy Storage on Smart Highways: A System Dynamics Approach for Dynamic Maintenance Decision-Making

Xiaochun Peng, Yanqun Yang
article en

Abstract

The resilience of Intelligent Transportation Systems (ITSs) heavily relies on distributed Battery Energy Storage Systems (BESSs) deployed in harsh, unattended highway environments. Traditional maintenance strategies often fail to account for the dynamic feedback between battery aging, environmental stress, and maintenance response latency. This study proposes a system dynamics (SD) framework to evaluate and optimize the resilience of these critical power infrastructures. By modeling the nonlinear interactions among sensor data, controller logic, and remote discharge terminals, we simulate the system’s dynamic behavior over a 36-month lifecycle. The results reveal a critical “scalability threshold”: when battery pack quantity exceeds 40 units, the system’s self-healing time increases disproportionately, degrading resilience. Furthermore, the study identifies 384 V as the optimal “Resilience Topology Voltage”, offering the fastest recovery speed by balancing thermal stability with consistency management efficiency. These findings provide theoretical guidelines for configuring BESS capacity and optimizing remote maintenance protocols to ensure uninterrupted highway operations.

EnergiesVol. 19(5)
Guangxi Science and Technology Department (CN), China Design Group (China) (CN), Fuzhou University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Advanced Battery Technologies Research
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Enhancing the Resilience of Distributed Energy Storage on Smart Highways: A System Dynamics Approach for Dynamic Maintenance Decision-Making — Xiaochun Peng, Yanqun Yang · Energies (2026) | TGRS Research Map | TGRS