Jorge Cortés
Professor
Cymer Corporation Endowed Chair
Decentralized Nash equilibrium learning by strategic generators
for economic dispatch
A. Cherukuri, J. Cortés
Proceedings of the American Control
Conference, Boston, Massachusetts, USA, 2016, pp. 1082-1087
Abstract
This paper studies an electricity market consisting of an
independent system operator (ISO) and a group of generators. The
goal is to solve the economic dispatch (ED) problem, i.e., make the
generators collectively meet a given amount of power demand while
minimizing the aggregate generation cost. The ISO by itself cannot
solve the ED problem as the generators are strategic and do not
share their cost functions. Instead, each generator submits to the
ISO the price per unit of electricity at which it is willing to
provide power to the ISO, which constitutes its bid. Based on the
bids, the ISO decides how much production to allocate to each
generator. The resulting Bertrand competition model defines the game
among the generators where the actions are the bids and the payoffs
are the profits. We provide a provably correct, decentralized
strategy, termed \inelasticalgo, that takes the generators' bids to
a neighborhood of the efficient Nash equilibrium and show that the
optimal production of the generators converges to the optimizer of
the ED problem. During the play, each generator only knows the
amount of power the ISO requests it to produce and is not aware of
the number of players, their actions, or their payoffs. Our
algorithm can be understood as ``learning via repeated play'', where
generators are ``myopically selfish'', changing their bid at each
iteration with the sole aim of maximizing their payoff.
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Mechanical and Aerospace Engineering,
University of California, San Diego
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cortes at ucsd.edu
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