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Energy saving potential of different setpoint control algorithms in mixed-mode buildings

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conference contribution
posted on 24.09.2018 by Charalampos Angelopoulos, Malcolm Cook, Eftychia Spentzou, Yash Shukla
Mixed-mode buildings can combine the use of natural and mechanical systems to achieve the desirable internal conditions. However, it is essential to effectively control a mixed-mode building to minimize the energy consumption without compromising the thermal comfort of the occupants. The aim of this research is to develop different setpoint control algorithms for mixed-mode buildings, by using a variety of adaptive methodologies such as ASHRAE Standard 55, IMAC model and EN15251, and evaluate their energy saving potential for Bangalore and Mumbai, India and Gatwick, UK. Cosimulations were used for this research. EnergyPlus was used to develop the building geometry and coupled with Modelica, where the control algorithms were developed. This is a novel simulation approach to assess control algorithms in buildings and provides great flexibility for future use of the control algorithms. The results showed that the effective control of mixed-mode building can result approximately in 40% energy saving in Indian cities compared to fully mechanical conditioned buildings whilst maintaining comfortable internal conditions for 90% of the year.

Funding

This research was financially supported by the Engineering and Physical Sciences Research Council (EPSRC) via the London-Loughborough Centre for Doctoral Training in Energy Demand (LoLo) (grant EP/L01517X/1) and via the research project Low Energy Cooling and Ventilation for Indian Residences (LECaVIR) (grant EP/P029450/1).

History

School

  • Architecture, Building and Civil Engineering

Published in

Building Simulation and Optimization 2018

Citation

ANGELOPOULOS, C. ... et al, 2018. Energy saving potential of different setpoint control algorithms in mixed-mode buildings. Presented at Building Simulation and Optimization 2018 (BSO18), Cambridge, UK, 11-12 September 2018.

Publisher

IBPSA

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

10/07/2018

Publication date

2018

Notes

This is a conference paper.

Publisher version

Language

en

Location

Emmanuel College, University of Cambridge

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