Method to Embed Behavioral Battery Model in Predictive Energy Management Systems

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Sutter, Axel
Gorecki, Tomasz T.
Bhoir, Shubham S.
In the context of battery use in an energy system, accurate degradation models are crucial to improve economic efficiency, because these models help to ensure that the cost of degradation is lower than the benefits of using the battery. This paper proposes a novel method to integrate a complex empirical degradation model of a lithium-ion battery into the optimization of an Energy Management System (EMS). The model uses relaxed nonlinear equations of a multi-factor degradation model that are based on empirical test data. This approach allows the degradation model to be included in an optimization framework and to monitor the State-of-Health (SoH) of the battery. The paper presents a case study where the proposed degra dation model is applied in an arbitrage scenario to evaluate the benefits of the model in the optimization process. The results show that even a simple degradation model yields a positive benefit of 6,250 EUR/MWh/year, while a more complex model can achieve up to 10,000 EUR/MWh/year. These findings demonstrate the efficacy of the proposed model in achieving efficient battery use in an energy system.
Publication Reference
ISGT Europe 2023, Grenoble, France
This work has received funding from the Swiss Federal Office of Energy under project BATMAESTRO