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Improved battery storage systems modeling for predictive energy management applications | IEEE Conference Publication | IEEE Xplore

Improved battery storage systems modeling for predictive energy management applications


Abstract:

This paper presents a model predictive control (MPC) framework for battery energy storage systems (BESS) management considering models for battery degradation, system eff...Show More

Abstract:

This paper presents a model predictive control (MPC) framework for battery energy storage systems (BESS) management considering models for battery degradation, system efficiency and V-I characteristics. The optimization framework has been tested for microgrids with different renewable generation and load mix considering several operation strategies. A comparison for one-year simulations between the proposed model and a naïve BESS model, show an increase in computation times that still allows the application of the framework for real-time control. Furthermore, a trade-off between financial revenue and reduced BESS degradation was evaluated for the yearly simulation, considering the degradation model proposed. Results show that a conservative BESS usage strategy can have a high impact on the asset’s lifetime and on the expected system revenues, depending on factors such as the objective function and the degradation threshold considered.
Date of Conference: 10-12 October 2022
Date Added to IEEE Xplore: 28 November 2022
ISBN Information:
Conference Location: Novi Sad, Serbia

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