Topology-aware predictive maintenance via joint replacement and reconfiguration for BESSs under heterogeneous capacity degradation

Abstract

Efficient maintenance of battery energy storage systems (BESS) is critical for reliable operation under large-scale renewable integration. In modular architectures, heterogeneous degradation creates strong interactions between component health and system topology, meaning system capacity and risk depend not only on individual states but also on dynamic module configuration. Conventional maintenance policies often assume a fixed mapping from component states to system performance and thus fail to address topology-induced bottlenecks and imbalance-driven risks, which frequently leads to premature replacements or hidden safety hazards. This study proposes a novel predictive maintenance (PdM) framework that synergistically coordinates module replacement and structural reconfiguration. Unlike existing approaches, our method treats maintenance as a coupled decision process where replacement restores component health while reconfiguration reshapes the topology to mitigate degradation constraints. The problem is formulated as a nested mixed-integer nonlinear programming (MINLP) model. To solve this computationally challenging problem, we develop a tailored Bayesian Hierarchical Optimization with Adaptive Large Neighborhood Search (BHO-ALNS) algorithm that efficiently explores the joint decision space of replacement thresholds and reconfiguration actions. Numerical experiments based on data-driven degradation simulations demonstrate that the proposed strategy significantly outperforms various common conventional schemes. Specifically, compared to the fixed-threshold replacement-only strategy frequently employed in real-world maintenance practice, our approach increases net economic benefit by approximately 23 percent, while simultaneously enhancing capacity utilization and mitigating safety risks. These findings highlight the necessity of jointly managing component degradation and system configuration, offering a paradigm shift from passive component renewal to active structural adaptation in BESS.

Keywords

BESS / PdM / heterogeneous degradation / replacement and reconfiguration / MINLP

RIGHTS & PERMISSIONS

Higher Education Press 2026

Just Accepted

This article has successfully passed peer review and final editorial review, and will soon enter typesetting, proofreading and other publishing processes. The currently displayed version is the accepted final manuscript. The officially published version will be updated with format, DOI and citation information upon launch. We recommend that you pay attention to subsequent journal notifications and preferentially cite the officially published version. Thank you for your support and cooperation.