Optimization and evaluation of operational and economic performance of grid-connected battery storage at different stages of battery health
Artikel i vetenskaplig tidskrift, 2025

Battery storage systems play a crucial role in modern energy infrastructure by enhancing grid flexibility. However, their long-term performance is limited by capacity degradation, which impacts operational efficiency and economic viability. This study proposes a degradation-aware optimization framework to evaluate the operational and economic performance of grid-connected battery systems across different stages of battery health, including new, mid-life, and near end-of-life conditions. The framework dynamically optimizes daily operational schedules, including cycle frequency, charge /discharge timing, and durations, in response to evolving degradation. The objective of optimization is to simultaneously maximize revenue and minimize degradation-related cost. The model incorporates both calendric and cyclic aging as functions of real-life operational conditions, ensuring informed and adaptive battery management. The results demonstrate that, despite a reduction in energy output per cycle from 95% in the first year to 77% near end-of-life, the proposed strategy stabilizes revenue across all stages by adjusting cycle characteristics. In the early stage, cycling is limited to once per day on over 80% of days, with extended charge/discharge durations (4–8 h) to mitigate initial degradation. In later stages, the strategy shifts to shorter charge/discharge durations (1–2 h) and increases the frequency to two cycles per day on up to 60% of days, thereby sustaining profitability. The findings offer valuable insights for grid operators, investors, and energy market participants in developing financially viable battery storage systems.

Dynamic operational strategies

Extending battery life

Maximizing economic returns

Real-life degradation modeling

Degradation-aware operation optimization

Grid-connected battery storage systems

Författare

Masoume Shabani

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik

Jinyue Yan

Hong Kong Polytechnic University

Energy Conversion and Management: X

25901745 (eISSN)

Vol. 27 101113

Ämneskategorier (SSIF 2025)

Energiteknik

Energisystem

DOI

10.1016/j.ecmx.2025.101113

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Senast uppdaterat

2025-07-08