TY - GEN
T1 - An efficient algorithm for optimal real-time pricing strategy in smart grid
AU - Zhang, Wang
AU - Chen, Guo
AU - Dong, Zhaoyang
AU - Li, Jueyou
AU - Wu, Zhiyou
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 - 2014/10/29
Y1 - 2014/10/29
N2 - The new dynamic pricing schemes encourage the consumers to participate more actively in the electricity energy market, and the smart meter and demand side management (DSM) make it possible. In this paper, we consider a smart grid environment with multiple users equipped with smart meters and energy management devices (EMD). An improved optimization method is proposed to maximize the social welfare of both users and the provider under a real-time pricing strategy. More specifically, we proposed a more practical and advanced gradient algorithm - fast distributed dual gradient algorithm (FDDGA). Compared with traditional distributed dual sub- gradient algorithm, this improved method does not only accelerate the convergence rate but also overcome the possible oscillation that caused by the uncertainty in choosing step size over iteration process in sub-gradient projection method. The simulation results also validate that the proposed algorithm is effective and efficient in solving the real time pricing problem for demand response. © 2014 IEEE.
AB - The new dynamic pricing schemes encourage the consumers to participate more actively in the electricity energy market, and the smart meter and demand side management (DSM) make it possible. In this paper, we consider a smart grid environment with multiple users equipped with smart meters and energy management devices (EMD). An improved optimization method is proposed to maximize the social welfare of both users and the provider under a real-time pricing strategy. More specifically, we proposed a more practical and advanced gradient algorithm - fast distributed dual gradient algorithm (FDDGA). Compared with traditional distributed dual sub- gradient algorithm, this improved method does not only accelerate the convergence rate but also overcome the possible oscillation that caused by the uncertainty in choosing step size over iteration process in sub-gradient projection method. The simulation results also validate that the proposed algorithm is effective and efficient in solving the real time pricing problem for demand response. © 2014 IEEE.
KW - demand side management
KW - distributed dual gradient algorithm
KW - dynamic pricing
KW - smart grid
UR - https://www.scopus.com/pages/publications/84930986782
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84930986782&origin=recordpage
U2 - 10.1109/PESGM.2014.6939401
DO - 10.1109/PESGM.2014.6939401
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781479964154
VL - 2014-October
T3 - IEEE Power and Energy Society General Meeting
BT - 2014 IEEE PES General Meeting / Conference and Exposition
PB - IEEE Computer Society
T2 - 2014 IEEE Power and Energy Society General Meeting
Y2 - 27 July 2014 through 31 July 2014
ER -