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Predictability of energy characteristics for cooling, ventilation and heating systems in sports facilities
NEC Laboratories Europe, NEC Europe Ltd., Heidelberg.
NEC Europe Ltd..
NEC Europe Ltd..
NEC Europe Ltd..
2015 (English)In: I2015 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT): Washington, DC , 18-20 Feb 2015, Piscataway, NJ: IEEE Communications Society, 2015Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we analyze operational energy data of the cooling, ventilation and heating systems of the professional soccer stadium Commerzbank Arena in Frankfurt, Germany. We analyze data collected over a six month period in 2014 statistically and show that depending on the stadium's operational context consumption patterns vary largely among the different systems resulting in very different behaviors. The results provide insights into what drives the energy consumption for different systems of a large commercial sports facility: the static heating system is purely dependent on outside air temperature, ventilation exhibits a pronounced daily consumption pattern irrespective of the temperature and cooling is driven by a combination of event operation and air temperature. These insights will allow us to predict, plan and balance the energy demands of different subsystems more accurately, resulting in energetic improvements of the stadium operation in the form of load shedding while maintaining the systems' service levels.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE Communications Society, 2015.
Keywords [en]
building services, cooling, energy consumption, facilities, heating, load shedding, sport, ventilation, Commerzbank arena, Frankfurt, Germany, air temperature, energy characteristic predictability, energy demand, soccer stadium, sports facility, static heating system, Buildings, Business, Context, Energy consumption, Heating, Ventilation, Context Awareness, Control Systems, Energy Management, Green Buildings, HVAC, Sports Stadium
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-30814DOI: 10.1109/ISGT.2015.7131848Scopus ID: 84939137908Local ID: 4c4bad1b-74a4-4cec-a1e7-bc03aa73fce2ISBN: 978-1-4799-1785-3 (electronic)OAI: oai:DiVA.org:ltu-30814DiVA, id: diva2:1004043
Conference
IEEE Power & Energy Society Innovative Smart Grid Technologies Conference : 18/02/2015 - 20/02/2015
Note
Upprättat; 2015; 20150921 (missch)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-02-26Bibliographically approved
In thesis
1. EVOX-CPS: A Methodology For Data-Driven Optimization Of Building Operation
Open this publication in new window or tab >>EVOX-CPS: A Methodology For Data-Driven Optimization Of Building Operation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Existing building stock’s energy efficiency must improve due to its significant proportion of the global energy consumption mix. Predictive building control promises to increase the efficiency of buildings during their operational phase and thus lead to a reduction of the lion’s share of buildings’ lifetime energy consumption. Predictive control complements other means to increase performance, such as refurbishments as well as modernization of systems.

This thesis contributes EVOX-CPS, a holistic methodology to develop data-driven predictive control for (existing) buildings and deploy the control in day-to-day use. EVOX-CPS evolves buildings into Cyber-Physical Systems and addresses the development of data-driven predictive control using computational methods. The thesis’ focus rests on accounting for the situation of existing buildings - which vary greatly regarding their physical characteristics, usage patterns, system installation, and instrumentation levels. The methodology addresses the aspect of building stock variety with its capability to flexibly adapt to different buildings’ characteristics, e.g., by supporting the integration of varying levels of pre-existing building instrumentation. Furthermore, EVOX-CPS supports using different data mining, regression, or control techniques (i) to strengthen the support for a variety of buildings, and (ii) to cater to researchers’ and practitioners’ differing skills, experiences, or preferences concerning different data analysis techniques. Through its flexibility, the methodology addresses a vast potential installation base and lowers the barriers for adoption in day-to-day use, e.g., by being able to leverage prior investments in building instrumentation and supporting different data-analysis techniques. At the same time, EVOX-CPS provides researchers and practitioners with comprehensive guidance relevant to their daily work. Besides, EVOX-CPS supports addressing a building’s known limitations in the daily operation, e.g., uncomfortable indoor conditions.

The experimentation in two real buildings validates the effectiveness of EVOX-CPS’ data-driven control with high reliability due to prolonged experimentation periods combined with applying energy normalization and inferential statistics. The experiments during routine heating system operation establish high confidence in the recorded effect sizes: the improvements in operational efficiency are profound and statistically significant. More specifically, the experiments of controlling the grass heating system of the soccer stadium Commerzbank Arena, Frankfurt, Germany, in two winters saved up to 66% (2014/2015) and 85% (2015/2016) of energy consumption. Extrapolation to an average heating season leads to expected savings of 775 MWh (148 t of CO2 emissions) and 1 GWh (197 t CO2), respectively. The experiments also show that EVOX-CPS allowed alleviating the known operational limitation of heating supply shortages which required nightly preheating in the stadium’s standard operating procedures. In another set of experiments, we applied the methodology to control the heating system of the Sierra Elvira School in Granada, Spain. The experimentation occurred during the regular class hours of 43 school days in winter 2015/2016. A first experiment demonstrated the possibility to lower consumption by one-third while maintaining indoor comfort. Another experiment raised average indoor temperatures by 2K with 5% additional energy consumption. Again, that illustrates EVOX-CPS’ capability to address a building’s known operational issues.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2018
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Keywords
Cyber-Physical Systems, Existing Buildings, Predictive Control, Sustainable Development, Energy Efficiency
National Category
Computer Sciences Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
urn:nbn:se:ltu:diva-67780 (URN)978-91-7790-059-7 (ISBN)978-91-7790-060-3 (ISBN)
Public defence
2018-04-27, Hörsal-A, Campus Skellefteå, Skellefteå, 08:30 (English)
Opponent
Supervisors
Available from: 2018-02-27 Created: 2018-02-26 Last updated: 2018-05-09Bibliographically approved

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