TY - GEN
T1 - A Markov process approach to ensemble control of smart buildings
AU - Pop, Roman
AU - Hassan, Ali
AU - Bruninx, Kenneth
AU - Chertkov, Michael
AU - Dvorkin, Yury
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this building. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer parameters, while also maintaining accuracy and feasibility sufficient for system-level analyses. Furthermore, the proposed Markov Process approach makes it possible to leverage real-time data streams available from intelligent building data acquisition systems, which are readily available in smart buildings, and merge it with physics-based and statistical models. Construction of the Markov Process naturally leads to a Markov Decision Process formulation, which describes optimal probabilistic control of a collection of similar buildings. The approach is illustrated using validated building data from Belgium.
AB - This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this building. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer parameters, while also maintaining accuracy and feasibility sufficient for system-level analyses. Furthermore, the proposed Markov Process approach makes it possible to leverage real-time data streams available from intelligent building data acquisition systems, which are readily available in smart buildings, and merge it with physics-based and statistical models. Construction of the Markov Process naturally leads to a Markov Decision Process formulation, which describes optimal probabilistic control of a collection of similar buildings. The approach is illustrated using validated building data from Belgium.
UR - http://www.scopus.com/inward/record.url?scp=85072339949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072339949&partnerID=8YFLogxK
U2 - 10.1109/PTC.2019.8810505
DO - 10.1109/PTC.2019.8810505
M3 - Conference contribution
T3 - 2019 IEEE Milan PowerTech, PowerTech 2019
BT - 2019 IEEE Milan PowerTech, PowerTech 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Milan PowerTech, PowerTech 2019
Y2 - 23 June 2019 through 27 June 2019
ER -