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Energy Efficiency Gains in Daily Grass Heating Operation of Sports Facilities through Supervisory Holistic Control
Luleå tekniska universitet, Institutionen för system- och rymdteknik, Datavetenskap. NEC Laboratories Europe, NEC Europe Ltd., Heidelberg.
NEC Laboratories Europe, NEC Europe Ltd., Heidelberg.
NEC Laboratories Europe, NEC Europe Ltd., Heidelberg.
NEC Laboratories Europe, NEC Europe Ltd., Heidelberg.
Antal upphovsmän: 42015 (Engelska)Ingår i: Buildsys'15: 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built, New York: ACM Digital Library, 2015, s. 85-94Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In recent reflections on environmental impacts of buildings, medium to large scale sports stadiums have gained substantial attention. These stadiums of e.g. professional soccer teams are characterized by special system installations like grass heating systems serving the crucial commercial asset(s) and by event-driven usage patterns. Public buildings of this size imply situation-specific operational modes combined with high levels of safety and comfort requirements. In this paper we provide experimental verification of the energy savings potential of a professional soccer stadium's grass heating system during day-to-day operation. Our supervisory holistic control based on state of the art information and communication technology (ICT) is verified by seven experiments which we executed within the real operational setup of the Commerzbank Arena in Frankfurt, Germany. Our experiments operated different control strategies of increasing complexity. In winter 2014/2015 we achieved weather normalized energy savings of more than 56% compared to the last heating season. In an average heating season this would amount to savings of approximately 780 MWh and 150 t CO2$. At the same time we violated minimum temperature targets less than 6% of the time. These results stress the feasibility and benefits of applying holistic context-aware control strategies to large scale legacy consumption systems using supervisory ICT platforms. We demonstrate significant efficiency improvements and establish a new energy baseline that future control strategy evolutions will have to benchmark against.

Ort, förlag, år, upplaga, sidor
New York: ACM Digital Library, 2015. s. 85-94
Nationell ämneskategori
Medieteknik
Forskningsämne
Distribuerade datorsystem
Identifikatorer
URN: urn:nbn:se:ltu:diva-20556DOI: 10.1145/2821650.2821661ISI: 000380608700010Scopus ID: 2-s2.0-84959052599Lokalt ID: 5ea67e1e-445e-47b5-a9c2-2e1866eaea16ISBN: 978-1-4503-3981-0 (tryckt)ISBN: 978-1-4503-3981-0 (digital)OAI: oai:DiVA.org:ltu-20556DiVA, id: diva2:993600
Konferens
2nd ACM International Conference on Embedded Systems for Energy-Efficient Built, Seoul, South Korea, Nov 4-5 2015
Anmärkning

Validerad; 2016; Nivå 1; 2016-10-06 (andbra)

Tillgänglig från: 2016-09-29 Skapad: 2016-09-29 Senast uppdaterad: 2018-07-10Bibliografiskt granskad
Ingår i avhandling
1. EVOX-CPS: A Methodology For Data-Driven Optimization Of Building Operation
Öppna denna publikation i ny flik eller fönster >>EVOX-CPS: A Methodology For Data-Driven Optimization Of Building Operation
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Luleå: Luleå University of Technology, 2018
Serie
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
Nyckelord
Cyber-Physical Systems, Existing Buildings, Predictive Control, Sustainable Development, Energy Efficiency
Nationell ämneskategori
Datavetenskap (datalogi) Medieteknik
Forskningsämne
Distribuerade datorsystem
Identifikatorer
urn:nbn:se:ltu:diva-67780 (URN)978-91-7790-059-7 (ISBN)978-91-7790-060-3 (ISBN)
Disputation
2018-04-27, Hörsal-A, Campus Skellefteå, Skellefteå, 08:30 (Engelska)
Opponent
Handledare
Tillgänglig från: 2018-02-27 Skapad: 2018-02-26 Senast uppdaterad: 2018-05-09Bibliografiskt granskad

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