TY - GEN
T1 - Coordinated energy scheduling for residential households in the smart grid
AU - Guo, Yuanxiong
AU - Pan, Miao
AU - Fang, Yuguang
AU - Khargonekar, Pramod 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 - 2012
Y1 - 2012
N2 - In this paper, we investigate the minimization of the total energy cost of multiple residential households in a smart grid neighborhood sharing a load serving entity. Specifically, each household may have renewable generation, energy storage as well as inelastic and elastic energy loads, and the load serving entity attempts to schedule the energy consumption of these households. To minimize the total energy cost in this neighborhood, we propose an online algorithm, called Lyapunov-based cost minimization algorithm (LCMA), which jointly considers the energy management and demand response decisions. We prove that LCMA can achieve close-to-optimal performance and is robust to the uncertainty of system dynamics. Numerical results based on the real-world trace data show its cost saving effectiveness. © 2012 IEEE.
AB - In this paper, we investigate the minimization of the total energy cost of multiple residential households in a smart grid neighborhood sharing a load serving entity. Specifically, each household may have renewable generation, energy storage as well as inelastic and elastic energy loads, and the load serving entity attempts to schedule the energy consumption of these households. To minimize the total energy cost in this neighborhood, we propose an online algorithm, called Lyapunov-based cost minimization algorithm (LCMA), which jointly considers the energy management and demand response decisions. We prove that LCMA can achieve close-to-optimal performance and is robust to the uncertainty of system dynamics. Numerical results based on the real-world trace data show its cost saving effectiveness. © 2012 IEEE.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84876029808&origin=recordpage
U2 - 10.1109/SmartGridComm.2012.6485970
DO - 10.1109/SmartGridComm.2012.6485970
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781467309110
T3 - 2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012
SP - 121
EP - 126
BT - 2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012
T2 - 2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012
Y2 - 5 November 2012 through 8 November 2012
ER -