| Download | - View author's version: Physics-aware degradation model of lithium-ion battery energy storage for techno-economic studies in power systems (PDF, 1.3 MiB)
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| DOI | Resolve DOI: https://doi.org/10.1109/TSTE.2023.3285453 |
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| Author | Search for: Vykhodtsev, Anton. V.1ORCID identifier: https://orcid.org/0000-0003-3275-3640; Search for: Jang, Darren2; Search for: Wang, Qianpu2; Search for: Rosehart, William1ORCID identifier: https://orcid.org/0000-0002-2974-6485; Search for: Zareipour, Hamidreza1ORCID identifier: https://orcid.org/0000-0003-2889-0386 |
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| Affiliation | - University of Calgary
- National Research Council Canada. Energy, Mining and Environment
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| Format | Text, Article |
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| Subject | degredation; batteries; computational modeling; aging; optimization; throughput; mathematical models |
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| Abstract | Power system operation and planning decisions for lithium-ion battery energy storage systems are mainly derived using their simplified linear models. While these models are computationally simple, they have limitations in how they estimate battery degradation, either using the energy throughput or the Rainflow method. This paper proposes a hybrid approach for lithium-ion battery system modeling suitable for use in power system studies that enhances representation of battery degradation at a reasonable computational cost. The proposed hybrid model combines a physics-based model for improved degradation estimates with a simple and linear energy reservoir model commonly used to represent a battery storage system. The advantage of constructing the battery model with this vision is that it allows its smooth integration into the mixed-integer optimization frameworks. The proposed model is evaluated using both power- and energy-based use cases from the electrical grid. The simulations demonstrate that degradation could be reduced by 45% compared to other modeling strategies while generating the same level of operation profits. The net result of using the proposed hybrid model could be an extended lifespan through better informed planning and operating decisions for energy storage assets. |
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| Publication date | 2023-06-16 |
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| Publisher | IEEE |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | f3551efa-d601-42ab-b5db-87be4485a90e |
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| Record created | 2023-09-06 |
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| Record modified | 2024-05-01 |
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