Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case

Simone Baldi

doi:10.1109/ICCA.2017.8003064

Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case

Simone Baldi

Team Bart De Schutter

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

2 Citations (Scopus)

Abstract

In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyberphysical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning feedback load management program that can operate on top of the rules. We demonstrate via extensive simulations the effectiveness of the program for intelligent management of the heating, ventilating and air conditioning (HVAC) loads so as to exploit renewable energy sources, while taking into account humanrelated
constraints like thermal comfort.

Original language	English
Title of host publication	Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA)
Editors	L. Liu, H. Lin
Place of Publication	Piscataway, NJ, USA
Publisher	IEEE
Pages	224-229
ISBN (Print)	978-1-5386-2679-5
DOIs	https://doi.org/10.1109/ICCA.2017.8003064
Publication status	Published - 2017
Event	ICCA 2017 13th International Conference on Control & Automation - Ohrid, Macedonia, The Former Yugoslav Republic of Duration: 3 Jul 2017 → 6 Jul 2017

Conference

Conference	ICCA 2017 13th International Conference on Control & Automation
Abbreviated title	ICCA 2017
Country/Territory	Macedonia, The Former Yugoslav Republic of
City	Ohrid
Period	3/07/17 → 6/07/17

Keywords

Demand-side management
Thermal comfort optimization
Occupancy information

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICCA.2017.8003064

Cite this

@inproceedings{67379dc791984e5780c04df78cd945d2,

title = "Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case",

abstract = "In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyberphysical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning feedback load management program that can operate on top of the rules. We demonstrate via extensive simulations the effectiveness of the program for intelligent management of the heating, ventilating and air conditioning (HVAC) loads so as to exploit renewable energy sources, while taking into account humanrelatedconstraints like thermal comfort.",

keywords = "Demand-side management, Thermal comfort optimization, Occupancy information",

author = "Simone Baldi",

year = "2017",

doi = "10.1109/ICCA.2017.8003064",

language = "English",

isbn = "978-1-5386-2679-5",

pages = "224--229",

editor = "L. Liu and H. Lin",

booktitle = "Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA)",

publisher = "IEEE",

address = "United States",

note = "ICCA 2017 13th International Conference on Control & Automation, ICCA 2017 ; Conference date: 03-07-2017 Through 06-07-2017",

}

Baldi, S 2017, Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case. in L Liu & H Lin (eds), Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA). IEEE, Piscataway, NJ, USA, pp. 224-229, ICCA 2017 13th International Conference on Control & Automation, Ohrid, Macedonia, The Former Yugoslav Republic of, 3/07/17. https://doi.org/10.1109/ICCA.2017.8003064

Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case. / Baldi, Simone.
Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA). ed. / L. Liu; H. Lin. Piscataway, NJ, USA: IEEE, 2017. p. 224-229.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Adaptive optimization for smart operation of cyber-physical systems

T2 - ICCA 2017 13th International Conference on Control & Automation

AU - Baldi, Simone

PY - 2017

Y1 - 2017

N2 - In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyberphysical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning feedback load management program that can operate on top of the rules. We demonstrate via extensive simulations the effectiveness of the program for intelligent management of the heating, ventilating and air conditioning (HVAC) loads so as to exploit renewable energy sources, while taking into account humanrelatedconstraints like thermal comfort.

AB - In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyberphysical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning feedback load management program that can operate on top of the rules. We demonstrate via extensive simulations the effectiveness of the program for intelligent management of the heating, ventilating and air conditioning (HVAC) loads so as to exploit renewable energy sources, while taking into account humanrelatedconstraints like thermal comfort.

KW - Demand-side management

KW - Thermal comfort optimization

KW - Occupancy information

U2 - 10.1109/ICCA.2017.8003064

DO - 10.1109/ICCA.2017.8003064

M3 - Conference contribution

SN - 978-1-5386-2679-5

SP - 224

EP - 229

BT - Proceedings of the 2017 13th IEEE International Conference on Control & Automation (ICCA)

A2 - Liu, L.

A2 - Lin, H.

PB - IEEE

CY - Piscataway, NJ, USA

Y2 - 3 July 2017 through 6 July 2017

ER -

Adaptive optimization for smart operation of cyber-physical systems: A thermostatic zoning test case

Abstract

Conference

Keywords

UN SDGs

Access to Document

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Cite this