• 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