TY - GEN
T1 - Capturing aggregate flexibility in Demand Response
AU - Alizadeh, Mahnoosh
AU - Scaglione, Anna
AU - Goldsmith, Andrea
AU - Kesidis, George
N1 - Publisher Copyright: © 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - Flexibility in electric power consumption can be leveraged by Demand Response (DR) programs. The goal of this paper is to systematically capture the inherent aggregate flexibility of a population of heterogenous small appliances in a reduced-order fashion. We do so by clustering individual loads based on their characteristics and service constraints. We highlight the challenges associated with learning the customer response to economic incentives while applying demand side management to heterogeneous appliances. We also develop a framework to quantify customer privacy in cluster-based direct load scheduling programs.
AB - Flexibility in electric power consumption can be leveraged by Demand Response (DR) programs. The goal of this paper is to systematically capture the inherent aggregate flexibility of a population of heterogenous small appliances in a reduced-order fashion. We do so by clustering individual loads based on their characteristics and service constraints. We highlight the challenges associated with learning the customer response to economic incentives while applying demand side management to heterogeneous appliances. We also develop a framework to quantify customer privacy in cluster-based direct load scheduling programs.
UR - https://www.scopus.com/pages/publications/84946086163
U2 - 10.1109/CDC.2014.7040399
DO - 10.1109/CDC.2014.7040399
M3 - Conference contribution
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 6439
EP - 6445
BT - 53rd IEEE Conference on Decision and Control,CDC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Y2 - 15 December 2014 through 17 December 2014
ER -