skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Distributed Flexibility Characterization and Resource Allocation Strategies for Multi-zone Commercial Buildings in the Smart Grid

Abstract

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 the neighboring zones. In this paper, we study a multi-agent based approach to model and control commercial building HVAC system for providing grid services. In the multi-agent system (MAS), 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 aggregated airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. Then, we propose a Nash-bargaining based airflow allocation strategy to track a dispatch signal (that is within the offered flexibility limit) while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition and average consensus. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than the centralized approaches especially when the system becomes larger and more complex.

Authors:
; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1254601
Report Number(s):
PNNL-SA-109049
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: 54th IEEE Conference on Decision and Control, December 15-18, 2015, Osaka, Japan, 3161-3168
Country of Publication:
United States
Language:
English

Citation Formats

Hao, He, Lian, Jianming, Kalsi, Karanjit, and Stoustrup, Jakob. Distributed Flexibility Characterization and Resource Allocation Strategies for Multi-zone Commercial Buildings in the Smart Grid. United States: N. p., 2015. Web. doi:10.1109/CDC.2015.7402693.
Hao, He, Lian, Jianming, Kalsi, Karanjit, & Stoustrup, Jakob. Distributed Flexibility Characterization and Resource Allocation Strategies for Multi-zone Commercial Buildings in the Smart Grid. United States. doi:10.1109/CDC.2015.7402693.
Hao, He, Lian, Jianming, Kalsi, Karanjit, and Stoustrup, Jakob. Tue . "Distributed Flexibility Characterization and Resource Allocation Strategies for Multi-zone Commercial Buildings in the Smart Grid". United States. doi:10.1109/CDC.2015.7402693.
@article{osti_1254601,
title = {Distributed Flexibility Characterization and Resource Allocation Strategies for Multi-zone Commercial Buildings in the Smart Grid},
author = {Hao, He and Lian, Jianming and Kalsi, Karanjit and Stoustrup, Jakob},
abstractNote = {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 the neighboring zones. In this paper, we study a multi-agent based approach to model and control commercial building HVAC system for providing grid services. In the multi-agent system (MAS), 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 aggregated airflow (and thus fan power) flexibility that the HVAC system can provide to the ancillary service market. Then, we propose a Nash-bargaining based airflow allocation strategy to track a dispatch signal (that is within the offered flexibility limit) while respecting the preference and flexibility of individual zones. Moreover, we devise a distributed algorithm to obtain the Nash bargaining solution via dual decomposition and average consensus. Numerical simulations illustrate that the proposed distributed protocols are much more scalable than the centralized approaches especially when the system becomes larger and more complex.},
doi = {10.1109/CDC.2015.7402693},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2015},
month = {12}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: