Mixed-Integer Real-time Control of a Building Energy Supply System
- We present a methodology based on mixed-integer nonlinear model predictive control for a real-time building energy management system in application to a single-family house with a combined heat and power (CHP) unit. The developed strategy successfully deals with the switching behavior of the system components as well as minimum admissible operating time constraints by use of a special switch-cost-aware rounding procedure. The quality of the presented solution is evaluated in comparison to the globally optimal dynamic programming method and conventional rule-based control strategy. Based on a real-world scenario, we show that our approach is more than real-time capable while maintaining high correspondence with the globally optimal solution. We achieve an average optimality gap of 2.5% compared to 20% for a conventional control approach, and are faster and more scalable than a dynamic programming approach.
Author: | Artyom BurdaORCiD, Dimitri BitnerORCiD, Felix BestehornORCiDGND, Christian KirchesORCiDGND, Martin GrotjahnORCiDGND |
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URN: | urn:nbn:de:bsz:960-opus4-24721 |
DOI: | https://doi.org/10.25968/opus-2472 |
DOI original: | https://doi.org/10.1109/LCSYS.2022.3229159 |
ISSN: | 2475-1456 |
Parent Title (English): | IEEE Control Systems Letters |
Publisher: | IEEE |
Document Type: | Article |
Language: | English |
Year of Completion: | 2022 |
Publishing Institution: | Hochschule Hannover |
Release Date: | 2023/03/13 |
Tag: | Building automation; Energy management; Model Predictive Control; Optimal control; mixed-integer nonlinear model predictive control |
GND Keyword: | Energiemanagement; Optimale Kontrolle; Modellprädiktive Regelung; Nichtlineare modellprädiktive Regelung |
Volume: | 7 |
Page Number: | 6 |
First Page: | 907 |
Last Page: | 912 |
Link to catalogue: | 1870850653 |
Institutes: | Fakultät II - Maschinenbau und Bioverfahrenstechnik |
DDC classes: | 620 Ingenieurwissenschaften und Maschinenbau |
Licence (German): | ![]() |