Virtual Power Plant Control for Large Residential Communities Using HVAC Systems for Energy Storage
Heating, ventilation, and air-conditioning (HVAC) systems use the most electricity of any household appliance in residential communities. HVAC system modeling facilitates the study of demand response (DR) at both the residential and power system levels. In this article, the equivalent thermal model of a reference house is proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. Energy storage capacity of HVAC systems is calculated and an equivalent state-of-charge is defined. The uniformity between HVAC systems and battery energy storage system is demonstrated by DR control. The aggregated HVAC load model is based on the reference house and considers a realistic distribution of HVAC parameters derived from one of the largest smart grid field demonstrators in rural America. A sequential DR scheme as part of a virtual power plant control is proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standards.
Digital Object Identifier (DOI)
The support of the Tennessee Valley Authority (TVA) and of University of Kentucky, the L. Stanley Pigman endowment is gratefully acknowledged.
Gong, Huangjie; Jones, Evan S.; Alden, Rosemary E.; Frye, Andrew G.; Colliver, Donald G.; and Ionel, Dan M., "Virtual Power Plant Control for Large Residential Communities Using HVAC Systems for Energy Storage" (2021). Power and Energy Institute of Kentucky Faculty Publications. 66.
Published in IEEE Transactions on Industry, v. 58, issue 1.
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The document available for download is the authors’ manuscript version accepted for publication. The final published version is copyrighted by IEEE and will be available as: “Gong, H., Jones, E. S., Alden, R. E., Frye, A. G., Colliver, D., and Ionel, D. M., Virtual Power Plant Control for Large Residential Communities using HVAC Systems for Energy Storage,” IEEE Transactions on Industry Applications, vol. 58, no. 1, pp. 622-633, Jan.-Feb. 2022, doi: 10.1109/TIA.2021.3120971.