TY - GEN
T1 - Distributed flexibility characterization and resource allocation for multi-zone commercial buildings in the smart grid
AU - Hao, He
AU - Lian, Jianming
AU - Kalsi, Karanjit
AU - Stoustrup, Jakob
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/2/8
Y1 - 2015/2/8
N2 - The HVAC (Heating, Ventilation, and Air-Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of its neighboring zones. In this paper, we study an agent-based approach to model and control commercial building HVAC system for providing ancillary services to the power grid. In the multi-agent-building-system (MABS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregate airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. A Nash-bargaining-based airflow allocation strategy is then proposed to track a dispatch signal while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than centralized approaches especially when the system becomes larger and more complex.
AB - The HVAC (Heating, Ventilation, and Air-Conditioning) system of commercial buildings is a complex system with a large number of dynamically interacting components. In particular, the thermal dynamics of each zone are coupled with those of its neighboring zones. In this paper, we study an agent-based approach to model and control commercial building HVAC system for providing ancillary services to the power grid. In the multi-agent-building-system (MABS), individual zones are modeled as agents that can communicate, interact, and negotiate with one another to achieve a common objective. We first propose a distributed characterization method on the aggregate airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. A Nash-bargaining-based airflow allocation strategy is then proposed to track a dispatch signal while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than centralized approaches especially when the system becomes larger and more complex.
UR - https://www.scopus.com/pages/publications/84962013787
U2 - 10.1109/CDC.2015.7402693
DO - 10.1109/CDC.2015.7402693
M3 - Conference contribution
AN - SCOPUS:84962013787
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 3161
EP - 3168
BT - 54rd IEEE Conference on Decision and Control,CDC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 54th IEEE Conference on Decision and Control, CDC 2015
Y2 - 15 December 2015 through 18 December 2015
ER -