Degradation-aware data-enabled predictive control of energy hubs

Journal Article (2023)
Author(s)

V. Behrunani

M. Zagorowska (ETH Zürich)

M. Hudoba de Badyn

F. Ricca

Philipp Heer

John Lygeros

DOI related publication
https://doi.org/10.1088/1742-6596/2600/7/072006 Final published version
More Info
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Publication Year
2023
Language
English
Issue number
7
Volume number
2600
Article number
072006
Pages (from-to)
072006
Downloads counter
152

Abstract

Mitigating the energy use in buildings, together with satisfaction of comfort requirements are the main objectives of efficient building control systems. Augmenting building energy systems with batteries can improve the energy use of a building, while posing the challenge of considering battery degradation during control operation. We demonstrate the performance of a data-enabled predictive control (DeePC) approach applied to a single multizone building and an energy hub comprising an electric heat pump and a battery. In a comparison with a standard rule-based controller, results demonstrate that the performance of DeePC is superior in terms of satisfaction of comfort constraints without increasing grid power consumption. Moreover, DeePC achieved two-fold decrease in battery degradation over one year, as compared to a rule-based controller.