{"type":"ScholarlyArticle","title":"Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning","authors":[{"name":"Marcello Fiducioso","slug":"marcello-fiducioso","given":"Marcello","family":"Fiducioso","affiliation":"Department of Computer Science , ETH Zurich , Switzerland; Building Technologies Division , Siemens Switzerland Ltd."},{"name":"Sebastian Curi","slug":"sebastian-curi","given":"Sebastian","family":"Curi","affiliation":"Department of Computer Science , ETH Zurich , Switzerland"},{"name":"Benedikt Schumacher","slug":"benedikt-schumacher","given":"Benedikt","family":"Schumacher","affiliation":"Building Technologies Division , Siemens Switzerland Ltd."},{"name":"Markus Gwerder","slug":"markus-gwerder","given":"Markus","family":"Gwerder","affiliation":"Building Technologies Division , Siemens Switzerland Ltd."},{"name":"Andreas Krause","slug":"andreas-krause","given":"Andreas","family":"Krause","affiliation":"Department of Computer Science , ETH Zurich , Switzerland"}],"abstract":"We tune one of the most common heating, ventilation, and air conditioning (HVAC) control loops, namely the temperature control of a room. For economical and environmental reasons, it is of prime importance to optimize the performance of this system. Buildings account from 20 to 40 % of a country energy consumption, and almost 50 % of it comes from HVAC systems. Scenario projections predict a 30 % decrease in heating consumption by 2050 due to efficiency increase. Advanced control techniques can improve performance; however, the proportional-integral-derivative (PID) control is typically used due to its simplicity and overall performance. We use Safe Contextual Bayesian Optimization to optimize the PID parameters without human intervention. We reduce costs by 32 % compared to the current PID controller setting while assuring safety and comfort to people in the room. The results of this work have an immediate impact on the room control loop performances and its related commissioning costs. Furthermore, this successful attempt paves the way for further use at different levels of HVAC systems, with promising energy, operational, and commissioning costs savings, and it is a practical demonstration of the positive effects that Artificial Intelligence can have on environmental sustainability.","doi":"10.24963/ijcai.2019/811","url":"https://ijcai.org/proceedings/2019/811","pdf":"https://ijcai.org/proceedings/2019/0811.pdf","markdown":"https://ijcai.org/proceedings/2019/811.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/811","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"AI for Improving Human Well-being","track":"AI for Improving Human Well-being","number":811,"pages":{"first":5850,"last":5856},"keywords":["Special Track on AI for Improving Human-Well Being: Computational sustainability (Special Track on AI and Human Wellbeing)"],"videos":[],"references":[{"position":1,"raw":"[Abdelrahman et al., 2016] Hany Abdelrahman, Felix Berkenkamp, Jan Poland, and Andreas Krause. 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