TY - GEN
T1 - Battery equivalent model for residential HVAC
AU - Dong, Jin
AU - Starke, Michael
AU - Cui, Borui
AU - Munk, Jeffrey
AU - Tsybina, Evgeniya
AU - Winstead, Christopher
AU - Xue, Yaosuo Sonny
AU - Olama, Mohammed
AU - Kuruganti, Teja
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8/2
Y1 - 2020/8/2
N2 - Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that the round-trip efficiency for providing grid services with HVAC systems can be close to 1. Inspired by this promising result, in this work, we rigorously develop a battery equivalent model (BEM) for residential HVAC systems. Relying only on typically available data, the proposed BEM will bridge the observability and controllability gaps between utility companies and customers. The proposed BEM will enable the utility companies to manage the flexible HVAC devices as easy as charging/discharging the conventional energy storage devices. Validated physics-based models are used to train the BEM, whose prediction accuracy is illustrated through a simulation study.
AB - Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that the round-trip efficiency for providing grid services with HVAC systems can be close to 1. Inspired by this promising result, in this work, we rigorously develop a battery equivalent model (BEM) for residential HVAC systems. Relying only on typically available data, the proposed BEM will bridge the observability and controllability gaps between utility companies and customers. The proposed BEM will enable the utility companies to manage the flexible HVAC devices as easy as charging/discharging the conventional energy storage devices. Validated physics-based models are used to train the BEM, whose prediction accuracy is illustrated through a simulation study.
UR - http://www.scopus.com/inward/record.url?scp=85099166995&partnerID=8YFLogxK
U2 - 10.1109/PESGM41954.2020.9281418
DO - 10.1109/PESGM41954.2020.9281418
M3 - Conference contribution
AN - SCOPUS:85099166995
T3 - IEEE Power and Energy Society General Meeting
BT - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020
PB - IEEE Computer Society
T2 - 2020 IEEE Power and Energy Society General Meeting, PESGM 2020
Y2 - 2 August 2020 through 6 August 2020
ER -