Abstract
Accurately modeling stationary battery storage behavior is crucial to understand and predict its limitations in demand-side management scenarios. In this paper, a lithium-ion battery model was derived to estimate lifetime and state-of-charge for building-integrated use cases. The proposed battery model aims to balance speed and accuracy when modeling battery behavior for real-time predictive control and optimization. In order to achieve these goals, a mixed modeling approach was taken, which incorporates regression fits to experimental data and an equivalent circuit to model battery behavior. A comparison of the proposed battery model output to actual data from the manufacturer validates the modeling approach taken in the paper. Additionally, a dynamic test case demonstrates the effects of using regression models to represent internal resistance and capacity fading.
Original language | American English |
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Number of pages | 9 |
State | Published - 2017 |
Event | IEEE Power and Energy Conference - Champaign, Illinois Duration: 23 Feb 2017 → 24 Feb 2017 |
Conference
Conference | IEEE Power and Energy Conference |
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City | Champaign, Illinois |
Period | 23/02/17 → 24/02/17 |
NREL Publication Number
- NREL/CP-5D00-67809
Keywords
- analytical models
- batteries
- buildings
- lithium-ion
- modeling
- optimization
- system integration