research-article

Reducing Energy Consumption for Space Heating by Changing Zone Temperature: Pilot Trial in Luleå, Sweden

Authors:

Sambaran BandhyopahyayAuthors Info & Claims

e-Energy '18: Proceedings of the Ninth International Conference on Future Energy Systems

Pages 266 - 270

https://doi.org/10.1145/3208903.3208918

Published: 12 June 2018 Publication History

Abstract

The commercial building sector constitutes a significant share (18%) of global energy consumption; HVAC accounts for 40% of that consumption. Thus, energy conservation in commercial buildings can help with reducing the operational cost, as well as decreasing global energy consumption. In this paper, we report findings from a field trial conducted in Luleå (Sweden), to reduce the energy consumption of a commercial office building, by varying the HVAC set-point temperature. We developed a data-driven model of the building's energy consumption to estimate baseline. The building model was further used for designing the field trials by performing a simulation of the energy consumption under varied set-point temperature schedules. Based on the simulation results, a two week trial was conducted. We found that overall energy consumption of the building can be reduced by 5.23% per °C reduction of set-point temperature. Moreover, we also collected thermal comfort feedback from the building occupant, and found that the comfort range of the occupants can be extended to the range of 21.5 °C to 23.5 °C than the currently used range of 22.0 °C to 22.5 °C

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Cited By

Veljkovic APohoryles DBournas D(2023)Heating energy demand estimation of the EU building stock: Combining building physics and artificial neural networksEnergy and Buildings10.1016/j.enbuild.2023.113474298(113474)Online publication date: Nov-2023
https://doi.org/10.1016/j.enbuild.2023.113474
Trivedi ABovornkeeratiroj PBreda JShenoy PTaneja JIrwin D(2020)Phone-based Ambient Temperature Sensing Using Opportunistic Crowdsensing and Machine LearningSustainable Computing: Informatics and Systems10.1016/j.suscom.2020.100479(100479)Online publication date: Nov-2020
https://doi.org/10.1016/j.suscom.2020.100479
Breda JTrivedi AWijesundara CBovornkeeratiroj PIrwin DShenoy PTaneja J(2019)Hot or NotProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360856(41-50)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3360322.3360856
Show More Cited By

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cover image ACM Conferences

e-Energy '18: Proceedings of the Ninth International Conference on Future Energy Systems

June 2018

657 pages

ISBN:9781450357678

DOI:10.1145/3208903

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 12 June 2018

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e-Energy '18: The Ninth International Conference on Future Energy Systems

June 12 - 15, 2018

Karlsruhe, Germany

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Overall Acceptance Rate 160 of 446 submissions, 36%

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Cited By

Veljkovic APohoryles DBournas D(2023)Heating energy demand estimation of the EU building stock: Combining building physics and artificial neural networksEnergy and Buildings10.1016/j.enbuild.2023.113474298(113474)Online publication date: Nov-2023
https://doi.org/10.1016/j.enbuild.2023.113474
Trivedi ABovornkeeratiroj PBreda JShenoy PTaneja JIrwin D(2020)Phone-based Ambient Temperature Sensing Using Opportunistic Crowdsensing and Machine LearningSustainable Computing: Informatics and Systems10.1016/j.suscom.2020.100479(100479)Online publication date: Nov-2020
https://doi.org/10.1016/j.suscom.2020.100479
Breda JTrivedi AWijesundara CBovornkeeratiroj PIrwin DShenoy PTaneja J(2019)Hot or NotProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360856(41-50)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3360322.3360856
Vishwanath AHong YBlake C(2019)Experimental Evaluation of a Data Driven Cooling Optimization Framework for HVAC Control in Commercial BuildingsProceedings of the Tenth ACM International Conference on Future Energy Systems10.1145/3307772.3328289(78-88)Online publication date: 15-Jun-2019
https://dl.acm.org/doi/10.1145/3307772.3328289
Vishwanath AChandan VSaurav K(2019)An IoT-Based Data Driven Precooling Solution for Electricity Cost Savings in Commercial BuildingsIEEE Internet of Things Journal10.1109/JIOT.2019.28979886:5(7337-7347)Online publication date: Oct-2019
https://doi.org/10.1109/JIOT.2019.2897988
Leung EColorado Escobar MStiubianu GJim SVyatskikh AFeng ZGarner NPatel PNaughton KFollador MKarshalev ETrexler MGorodetsky A(2019)A dynamic thermoregulatory material inspired by squid skinNature Communications10.1038/s41467-019-09589-w10:1Online publication date: 29-Apr-2019
https://doi.org/10.1038/s41467-019-09589-w

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