TY - GEN
T1 - Demand response through smart home energy management using thermal inertia
AU - Wang, Haiming
AU - Meng, Ke
AU - Luo, Fengji
AU - Dong, Zhao Yang
AU - Verbič, Gregor
AU - Xu, Zhao
AU - Wong, K. P.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2013
Y1 - 2013
N2 - In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid. © 2013 Australasian Committee for Power Engineering (ACPE).
AB - In this paper, the value of thermal inertia in demand response to benefit customers is determined through a Mixed Integer Linear Programming (MILP) algorithm. Thermal models with different sophistications for a smart house are investigated. The energy consumption for cooling a smart house is optimized to minimize the expenditure of cooling load. One parameter and two-parameter thermal models are integrated into the optimization. The optimization of thermal load for maintaining the smart house within thermal comfort level is formulated as a MILP algorithm under the dynamic pricing policy. It is observed that the utilization of thermal inertia could potentially benefit both smart house owners and grid operators in the context of smart grid. © 2013 Australasian Committee for Power Engineering (ACPE).
KW - Demand Response
KW - Mixed Integer Linear Programming
KW - Smart Home Energy Management System
KW - Thermal Inertia
UR - https://www.scopus.com/pages/publications/84894427543
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84894427543&origin=recordpage
U2 - 10.1109/aupec.2013.6725442
DO - 10.1109/aupec.2013.6725442
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781862959132
T3 - 2013 Australasian Universities Power Engineering Conference, AUPEC 2013
BT - 2013 Australasian Universities Power Engineering Conference, AUPEC 2013
T2 - 2013 Australasian Universities Power Engineering Conference, AUPEC 2013
Y2 - 29 September 2013 through 3 October 2013
ER -