TY - GEN
T1 - Efficient real-time residential energy management through MILP based rolling horizon optimization
AU - Wang, Haiming
AU - Meng, Ke
AU - Dong, Zhao Yang
AU - Xu, Zhao
AU - Luo, Fengji
AU - Wong, Kit Po
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 - 2015/9/30
Y1 - 2015/9/30
N2 - In this paper, a Mixed Integer Linear Programming (MILP) based rolling optimization approach under real time pricing (RTP) policy is introduced to efficiently manage energy consumption of a smart home equipped with a Battery Energy Storage System (BESS) and a solar PV system. Models of distributed energy resources (DERs) in a smart house are developed and accordingly optimal management of total energy consumption is formulated as a MILP problem, which is then solved by the MOSEK software platform. And a rolling optimization scheduling framework based on MILP is proposed to dispatch DERs within a smart home to minimize the expenditure under RTP policy. Case studies are conducted to validate the performance of the algorithm. It is observed that proposed algorithm could benefit both smart house owners and network operators technically and economically in the context of smart grid. © 2015 IEEE.
AB - In this paper, a Mixed Integer Linear Programming (MILP) based rolling optimization approach under real time pricing (RTP) policy is introduced to efficiently manage energy consumption of a smart home equipped with a Battery Energy Storage System (BESS) and a solar PV system. Models of distributed energy resources (DERs) in a smart house are developed and accordingly optimal management of total energy consumption is formulated as a MILP problem, which is then solved by the MOSEK software platform. And a rolling optimization scheduling framework based on MILP is proposed to dispatch DERs within a smart home to minimize the expenditure under RTP policy. Case studies are conducted to validate the performance of the algorithm. It is observed that proposed algorithm could benefit both smart house owners and network operators technically and economically in the context of smart grid. © 2015 IEEE.
KW - Demand Response
KW - Mixed Integer Linear Programming
KW - Rolling Optimization
KW - Smart Home Energy Management System
UR - https://www.scopus.com/pages/publications/84956866723
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84956866723&origin=recordpage
U2 - 10.1109/PESGM.2015.7285754
DO - 10.1109/PESGM.2015.7285754
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467380409
VL - 2015-September
T3 - IEEE Power and Energy Society General Meeting
BT - 2015 IEEE Power and Energy Society General Meeting, PESGM 2015
PB - IEEE Computer Society
T2 - IEEE Power and Energy Society General Meeting, PESGM 2015
Y2 - 26 July 2015 through 30 July 2015
ER -