Paper Info
Title
Efficient and scalable demand response for the smart power grid
Abstract
A demand response setup is considered entailing a set of appliances with deferrable and non-interruptible tasks. A mixed-integer linear programming model for scheduling the operational periods and power levels of the appliances is formulated in response to known dynamic pricing information with the objective of minimizing the total electricity cost and consumer dissatisfaction. A scalable algorithm yielding a near-optimal solution is developed by enforcing a separable structure, and using Lagrangian relaxation. Thus, the original problem is decomposed to per-appliance subproblems, which can be solved exactly based on dynamic programming. The proximal bundle method is employed to obtain a solution to the convexified version, which helps recovery of a primal feasible solution. Numerical tests validate the proposed approach.
Year
DOI
Venue
2011
10.1109/CAMSAP.2011.6135899
CAMSAP
Keywords
Field
DocType
scalable demand response,smart power grid,lagrangian relaxation,consumer dissatisfaction,integer programming,linear programming,electricity cost minimization,mixed-integer linear programming model,operational period scheduling,smart power grids,appliance power levels,efficient-demand response,dynamic programming,convexified version,dynamic pricing information,proximal bundle method,domestic appliances,pricing,power system economics
Dynamic programming,Mathematical optimization,Smart grid,Dynamic pricing,Computer science,Scheduling (computing),Demand response,Integer programming,Linear programming,Lagrangian relaxation
Conference
ISBN
Citations 
PageRank 
978-1-4577-2104-5
6
0.66
References 
Authors
6
2
Name
Order
Citations
PageRank
Seung-Jun Kim1100362.52
G. B. Giannakis2114641206.47