Issue |
E3S Web Conf.
Volume 111, 2019
CLIMA 2019 Congress
|
|
---|---|---|
Article Number | 04045 | |
Number of page(s) | 10 | |
Section | High Energy Performance and Sustainable Buildings, Simulation models and predictive tools for the buildings HVAC, IEQ and energy | |
DOI | https://doi.org/10.1051/e3sconf/201911104045 | |
Published online | 13 August 2019 |
Energy performance of air conditioned buildings based on short-term weather forecast
1 University of Niš, Faculty of Mechanical Engineering in Niš, 14 Aleksandra Medvedeva str, 18000, Niš, Serbia
2 University of Novi Sad, Faculty of Technical Sciences in Novi Sad, 6 Dositeja Obradovića square, 21000, Novi Sad, Serbia
3 University of Florence, Department of Architecture, via della Mattonaia n.14, Florence, Italy
* Corresponding author: marko.ignjatovic@masfak.ni.ac.rs; marko.ignjatovic@live.com
One of the possible ways to improve balance between building energy consumption and occupant thermal comfort in existing buildings is to use simulation-assisted operation of HVAC systems. Simulation-assisted operation can be formulated as a type of operation that implements knowledge of future disturbance acting on the building and that enables operating the systems in such a way to fulfill given goals, which in nature can often be contradictory. The most important future conditions on building energy consumption are weather parameters and occupant behavior and expectations of thermal environment. In order to achieve this type of operation, optimization methods must be applied. Methodology to create HVAC system operation strategies on a daily basis is presented. Methodology is based on using building energy performance simulation software EnergyPlus, available weather data, global sensitivity analysis, and custom developed software with particle swarm optimization method applied over the moving horizon. Global sensitivity analysis is used in order to reduce number of independent variables for the optimization process. The methodology is applied to office part of real combined-type building located in Niš, Serbia. Use of sensitivity analysis shows that the reduced number of independent variables for the optimization would lead to similar thermal comfort and energy consumption, with significant computer runtime reduction.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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