TY - GEN
T1 - Distributed load demand scheduling in smart grid to minimize electricity generation cost
AU - Yue, Siyu
AU - Zhu, Di
AU - Wang, Yanzhi
AU - Pedram, Massoud
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/29
Y1 - 2014/10/29
N2 - Load demand scheduling of electricity consumers is an effective way to alleviate the peak power demand on the electricity grid and to combat the mismatch between generation and consumption. In this paper, we consider a scenario where multiple users cooperate to perform load demand scheduling in order to minimize the electricity generation cost. With the help of a central controller in the grid, a globally optimal solution can be achieved. However, this centralized solution may not always be feasible since it requires a huge amount of communication and the grid may not be equipped with such a central controller at all. Therefore, we propose a distributed load demand scheduling algorithm where each end user schedules its own tasks based on the partial information provided by other users. Simulation results show that this distributed load demand scheduling is able to achieve near-optimal solutions that has very little performance degradation compared to the centralized method.
AB - Load demand scheduling of electricity consumers is an effective way to alleviate the peak power demand on the electricity grid and to combat the mismatch between generation and consumption. In this paper, we consider a scenario where multiple users cooperate to perform load demand scheduling in order to minimize the electricity generation cost. With the help of a central controller in the grid, a globally optimal solution can be achieved. However, this centralized solution may not always be feasible since it requires a huge amount of communication and the grid may not be equipped with such a central controller at all. Therefore, we propose a distributed load demand scheduling algorithm where each end user schedules its own tasks based on the partial information provided by other users. Simulation results show that this distributed load demand scheduling is able to achieve near-optimal solutions that has very little performance degradation compared to the centralized method.
UR - http://www.scopus.com/inward/record.url?scp=84930995207&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84930995207&partnerID=8YFLogxK
U2 - 10.1109/PESGM.2014.6939015
DO - 10.1109/PESGM.2014.6939015
M3 - Conference contribution
AN - SCOPUS:84930995207
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 -