Demand Response of HVACs in Large Residential Communities Based on Experimental Developments

Huangjie Gong; Evan S. Jones; Rosemary E. Alden; Andrew G. Frye; Donald Colliver; Dan M. Ionel

doi:10.1109/ECCE44975.2020.9235465

Demand Response of HVACs in Large Residential Communities Based on Experimental Developments

Huangjie Gong, Evan S. Jones, Rosemary E. Alden, Andrew G. Frye, Donald Colliver, Dan M. Ionel

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Scopus citations

Abstract

Heating, ventilation, and air-conditioning (HVAC) systems contribute the largest electricity usage for a residential community. Modeling of the HVAC systems facilitate the study of demand response (DR) at both the residential and the power system level. In this paper, the equivalent thermal model of a reference house was proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. The aggregated HVAC load was modeled based on the reference house while considering a realistic distribution of HVAC parameters derived from data that was provided by one of the largest smart grid field demonstrators in rural America. A sequential DR as part of a Virtual Power Plant (VPP) control was proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standard.

Original language	English
Title of host publication	ECCE 2020 - IEEE Energy Conversion Congress and Exposition
Pages	4545-4548
Number of pages	4
ISBN (Electronic)	9781728158266
DOIs	https://doi.org/10.1109/ECCE44975.2020.9235465
State	Published - Oct 11 2020
Event	12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020 - Virtual, Detroit, United States Duration: Oct 11 2020 → Oct 15 2020

Publication series

Name	ECCE 2020 - IEEE Energy Conversion Congress and Exposition

Conference

Conference	12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020
Country/Territory	United States
City	Virtual, Detroit
Period	10/11/20 → 10/15/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Funding

II. EXPERIMENTAL RESULTS AND DERIVATION OF HOUSE THERMAL MODEL PARAMETERS Beginning in 2008, TVA funded and managed a robotic house project with technical support from the Oak Ridge National Laboratory (ORNL). Robotic houses were constructed in a suburb of Knox County, TN in which the habitation of a family was physically simulated (Fig. 1). This project developed an analytical base for the energy optimization and new technology implementation at individual house level. A different initiative, the Smart Energy Technologies (SET) project based in Glasgow, KY, provided a testbed for the optimization of power flow at the community level.

Funders	Funder number
Oak Ridge National Laboratory
Tennessee Valley Authority

Keywords

Aggregated
Demand Response (DR)
Heating
Home Energy Management (HEM)
Smart Grids
Smart Home
Thermal Model
Virtual Power Plant (VPP)
and air-conditioning (HVAC)
ventilation

ASJC Scopus subject areas

Electrical and Electronic Engineering
Mechanical Engineering
Control and Optimization
Energy Engineering and Power Technology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ECCE44975.2020.9235465

Cite this

Gong, H., Jones, E. S., Alden, R. E., Frye, A. G., Colliver, D., & Ionel, D. M. (2020). Demand Response of HVACs in Large Residential Communities Based on Experimental Developments. In ECCE 2020 - IEEE Energy Conversion Congress and Exposition (pp. 4545-4548). Article 9235465 (ECCE 2020 - IEEE Energy Conversion Congress and Exposition). https://doi.org/10.1109/ECCE44975.2020.9235465

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abstract = "Heating, ventilation, and air-conditioning (HVAC) systems contribute the largest electricity usage for a residential community. Modeling of the HVAC systems facilitate the study of demand response (DR) at both the residential and the power system level. In this paper, the equivalent thermal model of a reference house was proposed. Parameters for the reference house were determined based on the systematic study of experimental data obtained from fully instrumented field demonstrators. The aggregated HVAC load was modeled based on the reference house while considering a realistic distribution of HVAC parameters derived from data that was provided by one of the largest smart grid field demonstrators in rural America. A sequential DR as part of a Virtual Power Plant (VPP) control was proposed to reduce both ramping rate and peak power at the aggregated level, while maintaining human comfort according to ASHRAE standard.",

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Gong, H, Jones, ES, Alden, RE, Frye, AG, Colliver, D & Ionel, DM 2020, Demand Response of HVACs in Large Residential Communities Based on Experimental Developments. in ECCE 2020 - IEEE Energy Conversion Congress and Exposition., 9235465, ECCE 2020 - IEEE Energy Conversion Congress and Exposition, pp. 4545-4548, 12th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2020, Virtual, Detroit, United States, 10/11/20. https://doi.org/10.1109/ECCE44975.2020.9235465

Demand Response of HVACs in Large Residential Communities Based on Experimental Developments. / Gong, Huangjie; Jones, Evan S.; Alden, Rosemary E. et al.
ECCE 2020 - IEEE Energy Conversion Congress and Exposition. 2020. p. 4545-4548 9235465 (ECCE 2020 - IEEE Energy Conversion Congress and Exposition).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Ionel, Dan M.

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ER -

Demand Response of HVACs in Large Residential Communities Based on Experimental Developments

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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Cite this