Economic Scheduling of Microgrids With a bi‐Level Model Considering Battery Aging

ABSTRACT Battery energy storage systems (BESS) are essential for smart grids but suffer from capacity degradation due to charging and discharging cycles, leading to significant costs. To optimize BESS operation, it is crucial to include battery degradation (BD) costs in scheduling, considering equivalent cycles and depth of discharge. This paper introduces a novel degradation cost model for optimal battery scheduling. A linear model based on a semi‐empirical approach represents the calendar aging process, and a new algorithm derived from the rainflow‐counting algorithm (RCA) calculates cycle aging based on the cycle life curve and state of charge during discharge. The degradation cost model is based on battery capacity fade and economic principles. Finally, a mixed‐integer bi‐level linear model (MIBLM) examines the interaction between distributed generation dispatch and BESS charging/discharging, assessing the feasibility of integrating BD cost into energy management. Results show that the proposed MIBLM considering BD significantly influences BESS strategies, reducing microgrid (MG) operation costs by 12.69% compared to single‐level models and achieving a 3.5% reduction in expenses compared to conventional strategies that ignore BD. The analysis also highlights the importance of considering calendar aging in determining optimal BESS capacity.

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Publication Details

Journal
Energy Storage
Published
2025-04-01
DOI
https://doi.org/10.1002/est2.70166
Citations
4
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
2.73
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article

Economic Scheduling of Microgrids With a bi‐Level Model Considering Battery Aging

Nguyen Pham, Linh Duy Nguyen, Minh Nguyen
4 citations
Energy Storage
Advanced Battery Technologies Research
2.73
article

Economic Scheduling of Microgrids With a bi‐Level Model Considering Battery Aging

Nguyen Pham, Linh Duy Nguyen, Minh Nguyen
article en
4 citations

Abstract

ABSTRACT Battery energy storage systems (BESS) are essential for smart grids but suffer from capacity degradation due to charging and discharging cycles, leading to significant costs. To optimize BESS operation, it is crucial to include battery degradation (BD) costs in scheduling, considering equivalent cycles and depth of discharge. This paper introduces a novel degradation cost model for optimal battery scheduling. A linear model based on a semi‐empirical approach represents the calendar aging process, and a new algorithm derived from the rainflow‐counting algorithm (RCA) calculates cycle aging based on the cycle life curve and state of charge during discharge. The degradation cost model is based on battery capacity fade and economic principles. Finally, a mixed‐integer bi‐level linear model (MIBLM) examines the interaction between distributed generation dispatch and BESS charging/discharging, assessing the feasibility of integrating BD cost into energy management. Results show that the proposed MIBLM considering BD significantly influences BESS strategies, reducing microgrid (MG) operation costs by 12.69% compared to single‐level models and achieving a 3.5% reduction in expenses compared to conventional strategies that ignore BD. The analysis also highlights the importance of considering calendar aging in determining optimal BESS capacity.

Energy StorageVol. 7(3)
Hanoi University of Science and Technology (VN)
Openalex Percentile: Top 11%
Advanced Battery Technologies Research
2.73
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