4.8 Article

Increasing the lifetime profitability of battery energy storage systems through aging aware operation

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APPLIED ENERGY
卷 348, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2023.121531

关键词

Battery energy storage system; Lithium-ion; Degradation model; Aging cost; Intraday trading; Energy arbitrage

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Lithium-ion cells degrade due to internal aging effects, which can affect the economics of battery energy storage systems. This study presents a model predictive control framework for designing aging aware operation strategies, allowing for benchmarking of optimization models and determination of the optimal aging cost. The results show that using this framework can significantly increase the lifetime profitability of a BESS compared to the prevalent approach. Furthermore, the study demonstrates that recent increases in electricity market prices have led to a substantial increase in achievable lifetime profit.
Lithium-ion cells are subject to degradation due to a multitude of cell-internal aging effects, which can significantly influence the economics of battery energy storage systems (BESS). Since the rate of degradation depends on external stress factors such as the state-of-charge, charge/discharge-rate, and depth of cycle, it can be directly influenced through the operation strategy. In this contribution, we propose a model predictive control (MPC) framework for designing aging aware operation strategies. By simulating the entire BESS lifetime on a digital twin, different aging aware optimization models can be benchmarked and the optimal value for aging cost can be determined. In a case study, the application of generating profit through arbitrage trading on the EPEX SPOT intraday electricity market is investigated. For that, a linearized model for the calendar and cyclic capacity loss of a lithium iron phosphate cell is presented. The results show that using the MPC framework to determine the optimal aging cost can significantly increase the lifetime profitability of a BESS, compared to the prevalent approach of selecting aging cost based on the cost of the battery system. Furthermore, the lifetime profit from energy arbitrage can be increased by an additional 24.9% when using the linearized calendar degradation model and by 29.3% when using both the linearized calendar and cyclic degradation model, compared to an energy throughput based aging cost model. By examining price data from 2019 to 2022, the case study demonstrates that the recent increases in prices and price fluctuations on wholesale electricity markets have led to a substantial increase of the achievable lifetime profit.

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