Paper Info
Title
Real-time electricity pricing for demand response using online convex optimization
Abstract
Real-time electricity pricing strategies for demand response in smart grids are proposed. By accounting for individual consumers' responsiveness to prices, adjustments are made so as to induce desirable usage behavior and reduce peaks in load curves. An online convex optimization framework is adopted, which provides performance guarantees with minimal assumptions on the dynamics of load levels and consumer responsiveness. Two feedback structures are considered: a full information setup, where aggregate load levels as well as individual price elasticity parameters are directly available; and a partial information (bandit) case, where only the load levels are revealed. Fairness and sparsity constraints are also incorporated. Numerical tests verify the effectiveness of the proposed approach.
Year
DOI
Venue
2014
10.1109/ISGT.2014.6816447
ISGT
Keywords
Field
DocType
usage behavior,consumer responsiveness,numerical test,online convex optimization framework,partial information case,load curves,real-time electricity pricing strategy,convex programming,demand response,bandit case,feedback structures,aggregate load level,smart power grids,load level dynamics,sparsity constraint,full information setup,peak reduction,pricing,power system economics,price elasticity parameter,smart grids,real time systems,convex functions,elasticity
Load management,Economics,Mathematical optimization,Smart grid,Price elasticity of demand,Demand response,Convex function,Convex optimization,Elasticity (economics),Electricity pricing
Conference
Citations 
PageRank 
References 
10
0.54
10
Authors
2
Name
Order
Citations
PageRank
Seung-Jun Kim1100362.52
G. B. Giannakis2114641206.47