Optimal Operation of a Building with Electricity-Heat Networks and Seasonal Storage
<|reference_start|>Optimal Operation of a Building with Electricity-Heat Networks and Seasonal Storage: As seasonal thermal energy storage emerges as an efficient solution to reduce CO2 emissions of buildings, challenges appear related to its optimal operation. In a system including short-term electricity storage, long-term heat storage, and where electricity and heat networks are connected through a heat pump, it becomes crucial to operate the system on two time scales. Based on real data from a university building, we simulate the operation of such a system over a year, comparing different strategies based on model predictive control (MPC). The first objective of this paper is to determine the minimum prediction horizon to retrieve the results of the full-horizon operation problem with cost minimization. The second objective is to evaluate a method that combines MPC with setting targets on the heat storage level at the end of the prediction horizon, based on historical data. For a prediction horizon of 6 days, the suboptimality gap with the full-horizon results is 4.31%, compared to 11.42% when using a prediction horizon of 42 days and fixing the final level to be equal to the initial level, which is a common approach.<|reference_end|>
@article{prat2024optimal,
    title={Optimal Operation of a Building with Electricity-Heat Networks and
  Seasonal Storage},
    author={El'ea Prat, Pierre Pinson, Richard M. Lusby, Riwal Plougonven, Jordi
  Badosa, Philippe Drobinski},
    journal={arXiv preprint arXiv:2409.08721},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.08721},
    primaryClass={eess.SY cs.SY math.OC}
}