We consider the setting in which generators compete in scalar-parameterized supply functions to serve an inelastic demand spread throughout a transmission constrained power network. The market clears according to a locational marginal pricing mechanism, in which the independent system operator (ISO) determines the generators' production quantities so as to minimize the revealed cost of meeting demand, subject to transmission and generator capacity constraints. Under the assumption that both the ISO and generators choose their strategies simultaneously, we establish the existence of Nash equilibria for the underlying game, and derive a tight bound on its price of anarchy. Under the more restrictive setting of a two-node power network, we present a detailed comparison of market outcomes predicted by the simultaneous-move formulation of the game against those predicted by the more plausible sequential-move formulation, where the ISO observes the generators' strategy profile prior to determining their production quantities.

%B 2016 IEEE 55th Conference on Decision and Control (CDC) %I IEEE %C Las Vegas, NV, USA %P 1542 - 1548 %8 12/2016 %R 10.1109/CDC.2016.7798485 %0 Conference Paper %B 2016 American Control Conference (ACC) %D 2016 %T Performance bounds for robust decentralized control %A Weixuan Lin %A Eilyan Bitar %K RM14-002 %XWe consider the decentralized output feedback control of stochastic linear systems, subject to robust linear constraints on both the state and input trajectories. For problems with partially nested information structures, we establish an upper bound on the minimum achievable cost by computing the optimal affine decentralized control policy as a solution to a finite-dimensional conic program. For problems with general (possibly nonclassical) information structures, we construct another finite-dimensional conic program whose optimal value stands as a lower bound on the minimum achievable cost. With this lower bound in hand, one can bound the suboptimality incurred by any feasible decentralized control policy. A study of a partially nested system reveals that affine policies can be close to optimal, even in the presence state/input constraints and non-Gaussian disturbances.

%B 2016 American Control Conference (ACC) %I IEEE %C Boston, MA, USA %P 4323 - 4330 %8 08/2016 %R 10.1109/ACC.2016.7525602