Abstract
Abstract
In the context of building electrification, the operation of distributed energy resources integrating multiple energy carriers (electricity, heat, mobility) poses a significant challenge due to the nonlinear device dynamics, uncertainty, and computational issues. As such, energy management systems seek to decide the power dispatch in the best way possible. The objective is to minimize and balance operative costs (energy bills or asset degradation) with user requirements (mobility, heating, etc.). Current energy management uses empirical battery ageing models outside of their specific fitting conditions, resulting in inaccuracies and poor performance. Moreover, the link to thermal systems is also overlooked. This paper presents an ageing-aware nonlinear economic model predictive controller for electrified buildings that incorporates physics-based battery ageing models. The models distinguish between energy storage systems (chemistry, ageing state, etc.) and make explicit the trade-off between grid cost and battery degradation. The proposed algorithm can either cut down on grid costs or extend battery lifetime (electric vehicle or stationary battery packs). Additionally, substituting NMC cells with LFP chemistries optimizes grid performance during the summer, yielding a 10% grid cost reduction and a 20% decrease in degradation. Finally, the grid cost and degradation of the presented MPC when using aged batteries are improved with respect to the state of the art by 10% and 5% respectively, in periods with high solar generation and low thermal loads like summer.
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@article{Slaifstein2026Ageing,
title = {Ageing-aware energy management for residential multi-carrier energy systems},
author = {Darío Slaifstein and Gautham Ram Chandra Mouli and Laura Ramírez-Elizondo and Pavol Bauer},
journal = {Journal of Energy Storage},
year = {2026},
doi = {10.1016/j.est.2026.122889},
url = {https://doi.org/10.1016/j.est.2026.122889}
}
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