TY - GEN
T1 - Scalable model predictive control of demand for ancillary services
AU - Alizadeh, Mahnoosh
AU - Scaglione, Anna
AU - Kesidis, George
PY - 2013/12/1
Y1 - 2013/12/1
N2 - In this paper, we develop an integrated decision making framework for the planning and real-time control decisions made by a Load Serving Entity (LSE) providing ancillary services to the wholesale market. Due to the multi-settlement structure of the energy market, planning decisions by the LSE are naturally made at multiple temporal stages. The tight interdependence among decisions demands an integrated approach to minimize the overall costs of operation. In order to model the dynamics of the load at large-scales when making these decisions, we propose a classification-based model that captures the effect of scheduling decisions made for individual appliances at aggregate levels, with reasonable effort. To provide a tangible example of how this load aggregation technique can be applied, we study the case of Electric Vehicle (EV) charging in detail.
AB - In this paper, we develop an integrated decision making framework for the planning and real-time control decisions made by a Load Serving Entity (LSE) providing ancillary services to the wholesale market. Due to the multi-settlement structure of the energy market, planning decisions by the LSE are naturally made at multiple temporal stages. The tight interdependence among decisions demands an integrated approach to minimize the overall costs of operation. In order to model the dynamics of the load at large-scales when making these decisions, we propose a classification-based model that captures the effect of scheduling decisions made for individual appliances at aggregate levels, with reasonable effort. To provide a tangible example of how this load aggregation technique can be applied, we study the case of Electric Vehicle (EV) charging in detail.
UR - http://www.scopus.com/inward/record.url?scp=84893532047&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893532047&partnerID=8YFLogxK
U2 - 10.1109/SmartGridComm.2013.6688038
DO - 10.1109/SmartGridComm.2013.6688038
M3 - Conference contribution
AN - SCOPUS:84893532047
SN - 9781479915262
T3 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
SP - 684
EP - 689
BT - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
T2 - 2013 IEEE International Conference on Smart Grid Communications, SmartGridComm 2013
Y2 - 21 October 2013 through 24 October 2013
ER -