DocumentCode :
3535693
Title :
Day ahead dynamic pricing for demand response in dynamic environments
Author :
Liyan Jia ; Lang Tong
Author_Institution :
Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
5608
Lastpage :
5613
Abstract :
The problem of optimizing retail pricing of electricity for price-responsive dynamic loads is considered. For the class of day-ahead dynamic prices (DADPs), the problem of retail pricing is modeled as a Stackelberg game with the retailer as the leader and its customers the followers. It is shown that the optimal customer response to a DADP has an affine structure with a deterministic negative definite sensitivity matrix and a stochastic bias. With this structure, tradeoffs between consumer surplus and retail profit can be characterized by a convex region with a concave and non-increasing Pareto front, each point on the Pareto front corresponding to an equilibrium in a dynamic game with a particular payoff function; any consumer surplus-retail profit pair above the Pareto front is not attainable by any dynamic pricing scheme. The optimal DADP that maximizes the social welfare is shown to be that maximizes the consumer surplus thus making retail profit zero. Effects of renewable energy are also considered.
Keywords :
Pareto optimisation; concave programming; convex programming; game theory; matrix algebra; power system economics; pricing; renewable energy sources; smart power grids; DADP; Stackelberg game; affine structure; concave programming; consumer surplus; convex region; day ahead dynamic pricing; demand response; deterministic negative definite sensitivity matrix; electricity retail pricing optimization; nonincreasing Pareto front; optimal customer response; payoff function; price-responsive dynamic loads; renewable energy effects; retail profit; social welfare; stochastic bias; Games; Load management; Optimization; Pricing; Real-time systems; Uncertainty; Wind power generation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760773
Filename :
6760773
Link To Document :
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