TY - JOUR
T1 - Optimizing commercial building participation in energy and ancillary service markets
AU - Pavlak, Gregory S.
AU - Henze, Gregor P.
AU - Cushing, Vincent J.
N1 - Funding Information:
This work has been sponsored through a research contract with QCoefficient, Inc., for which the authors would like to express their sincere gratitude. Moreover, G.P. Henze discloses his role as technology advisor and co-founder of QCoefficient, Inc. This work utilized the Janus supercomputer, which is supported by the National Science Foundation (award number CNS-0821794) and the University of Colorado Boulder. The Janus supercomputer is a joint effort of the University of Colorado Boulder, the University of Colorado Denver, and the National Center for Atmospheric Research.
PY - 2014/10
Y1 - 2014/10
N2 - Providing ancillary services through flexible load response has the potential to increase electric grid reliability and efficiency while offering loads a revenue generating opportunity. The large power draw of commercial buildings, along with thermal mass characteristics, has sparked interest in providing ancillary services through intelligent operation of building mechanical systems. As a precursor to participating in ancillary service markets, the quantity of service available must be estimated. This work presents a model-based approach for estimating commercial building frequency regulation capability. A model predictive control framework is proposed to determine optimal operating strategies in consideration of energy use, energy expense, peak demand, economic demand response revenue, and frequency regulation revenue. The methodology is demonstrated through simulation for medium office and large office building applications, highlighting its ability to merge revenue generating opportunities with traditional demand and cost reducing objectives.
AB - Providing ancillary services through flexible load response has the potential to increase electric grid reliability and efficiency while offering loads a revenue generating opportunity. The large power draw of commercial buildings, along with thermal mass characteristics, has sparked interest in providing ancillary services through intelligent operation of building mechanical systems. As a precursor to participating in ancillary service markets, the quantity of service available must be estimated. This work presents a model-based approach for estimating commercial building frequency regulation capability. A model predictive control framework is proposed to determine optimal operating strategies in consideration of energy use, energy expense, peak demand, economic demand response revenue, and frequency regulation revenue. The methodology is demonstrated through simulation for medium office and large office building applications, highlighting its ability to merge revenue generating opportunities with traditional demand and cost reducing objectives.
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U2 - 10.1016/j.enbuild.2014.05.048
DO - 10.1016/j.enbuild.2014.05.048
M3 - Article
AN - SCOPUS:84903722223
SN - 0378-7788
VL - 81
SP - 115
EP - 126
JO - Energy and Buildings
JF - Energy and Buildings
ER -