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Syst."],"published-print":{"date-parts":[[2018,10,31]]},"abstract":"<jats:p>\n            The environmental impacts of medium to large-scale buildings receive substantial attention in research, industry, and media. This article studies the energy savings potential of a commercial soccer stadium during day-to-day operation. Buildings of this kind are characterized by special purpose system installations like grass heating systems and by event-driven usage patterns. This work presents a methodology to holistically analyze the stadium\u2019s characteristics and integrate its existing instrumentation into a Cyber-Physical System, enabling to deploy different control strategies flexibly. In total, seven different strategies for controlling the studied stadium\u2019s grass heating system are developed and tested in operation. Experiments in winter season 2014\/2015 validated the strategies\u2019 impacts within the real operational setup of the\n            <jats:italic>Commerzbank Arena<\/jats:italic>\n            , Frankfurt, Germany. With 95% confidence, these experiments saved up to 66% of median daily weather-normalized energy consumption. Extrapolated to an average heating season, this corresponds to savings of 775MWh and 148t of CO\n            <jats:sub>2<\/jats:sub>\n            emissions. In winter 2015\/2016 an additional predictive nighttime heating experiment targeted lower temperatures, which increased the savings to up to 85%, equivalent to 1GWh (197t CO\n            <jats:sub>2<\/jats:sub>\n            ) in an average winter. Beyond achieving significant energy savings, the different control strategies also met the target temperature levels to the satisfaction of the stadium\u2019s operational staff. While the case study constitutes a significant part, the discussions dedicated to the transferability of this work to other stadiums and other building types show that the concepts and the approach are of general nature. Furthermore, this work demonstrates the first successful application of Deep Belief Networks to regress and predict the thermal evolution of building systems.\n          <\/jats:p>","DOI":"10.1145\/3140235","type":"journal-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T19:19:10Z","timestamp":1530818350000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Cyber-Physical System for Energy-Efficient Stadium Operation"],"prefix":"10.1145","volume":"2","author":[{"given":"Mischa","family":"Schmidt","sequence":"first","affiliation":[{"name":"NEC Laboratories Europe, Lule\u00e5\u00a0University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anett","family":"Sch\u00fclke","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alberto","family":"Venturi","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roman","family":"Kurpatov","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Enrique Blanco","family":"Henr\u00edquez","sequence":"additional","affiliation":[{"name":"NEC Laboratories Europe, Heidelberg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,7,5]]},"reference":[{"volume-title":"Proceedings of the Deep Learning and Unsupervised Feature Learning Workshop (NIPS\u201912)","year":"2012","author":"Bastien Fr\u00e9d\u00e9ric","key":"e_1_2_1_1_1"},{"key":"e_1_2_1_2_1","first-page":"4","article-title":"Turfgrass root basics","volume":"9","author":"Beard James B.","year":"2001","journal-title":"TURFAX"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00703-010-0104-x"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-012-2557-5"},{"volume-title":"Retrieved","year":"2015","author":"\u00fcr Wirtschaft Bundesministerium","key":"e_1_2_1_5_1"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2015.01.023"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.segan.2016.02.002"},{"key":"e_1_2_1_8_1","unstructured":"Deutsches Institut f\u00fcr Normierung. 2003-2014. 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