Abstract
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.
| Original language | English (US) |
|---|---|
| Article number | 7040399 |
| Pages (from-to) | 6439-6445 |
| Number of pages | 7 |
| Journal | Unknown Journal |
| Volume | 2015-February |
| Issue number | February |
| DOIs | |
| State | Published - 2014 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization
Cite this
Capturing aggregate flexibility in Demand Response. / Alizadeh, Mahnoosh; Scaglione, Anna; Goldsmith, Andrea; Kesidis, George.
In: Unknown Journal, Vol. 2015-February, No. February, 7040399, 2014, p. 6439-6445.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Capturing aggregate flexibility in Demand Response
AU - Alizadeh, Mahnoosh
AU - Scaglione, Anna
AU - Goldsmith, Andrea
AU - Kesidis, George
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 - http://www.scopus.com/inward/record.url?scp=84946086163&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946086163&partnerID=8YFLogxK
U2 - 10.1109/CDC.2014.7040399
DO - 10.1109/CDC.2014.7040399
M3 - Article
AN - SCOPUS:84946086163
VL - 2015-February
SP - 6439
EP - 6445
JO - Scanning Electron Microscopy
JF - Scanning Electron Microscopy
SN - 0586-5581
IS - February
M1 - 7040399
ER -