Journals: Noncooperative Day-Ahead Bidding Strategies for Demand-Side Expected Cost Minimization with Real-Time Adjustments: A GNEP Approach
Atzeni, L. García Ordóñez, Scutari, D. Pérez Palomar and J. Rodríguez Fonollosa

Abstract

The envisioned smart grid aims at improving the
interaction between the supply- and the demand-side of the
electricity network, creating unprecedented possibilities for optimizing
the energy usage at different levels of the grid. In
this paper, we propose a distributed demand-side management
(DSM) method intended for smart grid users with load prediction
capabilities, who possibly employ dispatchable energy generation
and storage devices. These users participate in the day-ahead
market and are interested in deriving the bidding, production,
and storage strategies that jointly minimize their expected
monetary expense. The resulting day-ahead grid optimization is
formulated as a generalized Nash equilibrium problem (GNEP),
which includes global constraints that couple the users’ strategies.
Building on the theory of variational inequalities, we study the
main properties of the GNEP and devise a distributed, iterative
algorithm converging to the variational solutions of the GNEP.
Additionally, users can exploit the reduced uncertainty about
their energy consumption and renewable generation at the time
of dispatch. We thus present a complementary DSM procedure
that allows them to perform some unilateral adjustments on their
generation and storage strategies so as to reduce the impact
of their real-time deviations with respect to the amount of
energy negotiated in the day-ahead. Finally, numerical results
in realistic scenarios are reported to corroborate the proposed
DSM technique.


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