Talks and Poster Presentations (with Proceedings-Entry):
M. Zauner, M. Killian, L. Böhler, M. Kozek, R. Goldgruber, A. Leitner et al.:
"Smart home management system with extensive disturbance predictions";
Talk: e-nova 2018 Internationaler Kongress: Gebäude der Zukunft? vernetzt - digital - ökosozial,
Pinkafeld;
2018-11-22
- 2018-11-23; in: "enova 2018",
M. Zauner (ed.);
Leykam,
Gebäude der Zukunft? vernetzt - digital - ökosozial
(2018),
ISBN: 978-3-7011-0420-8;
113
- 120.
English abstract:
Minimizing the energy consumption of residential buildings while providing maximal thermal comfort is a current challenge. In this paper a smart home management system is proposed which is able to globally optimize the thermal and electrical systems of a modern smart home, instead of locally optimizing each subsystem alone. The used controller consists of a mixed-integer quadratic program (MIQP) used in a model predictive controller (MPC) scheme. The MIQP-MPC is capable of handling multiple energy sources, respecting external grid-based constraints, as well as handling the electrical heating systems. Furthermore, extensive dis-turbance prediction methods for the most influencing external and internal disturbances of a smart home are presented. Those disturbances are ambient temperature, solar irradiation and occupancy. With the predictions of the future occupancy, the MIQP-MPC is also able to heat the building only when needed. The MIQP-MPC can help future smart grids to reduce the peak loads and can act as an energy storage, if grid-side energy production is high. An-other feature of the proposed controller is a simple-to-use interface for the end-user. This interface enables the end-users to tune the controller in an intuitive way to their individual demands. Therefore, the end-user is able to balance the partially conflicting goals of the MIQP-MPC. Those goals are the reduction of running costs, the maximal usage of renewable energy sources, and the minimisation of the temperature deviation from the set point.
Keywords:
smart homes; model predictive; disturbance predictions; optimization;
Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_274498.docx
Created from the Publication Database of the Vienna University of Technology.