TY - CONF
T1 - Parameterized supply function equilibrium in power networks
T2 - 2016 IEEE 55th Conference on Decision and Control (CDC)
Y1 - 2016/12//
SP - 1542
EP - 1548
A1 - Weixuan Lin
A1 - Eilyan Bitar
KW - RM14-002
AB - 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.
JF - 2016 IEEE 55th Conference on Decision and Control (CDC)
PB - IEEE
CY - Las Vegas, NV, USA
DO - 10.1109/CDC.2016.7798485
ER -
TY - CONF
T1 - Performance bounds for robust decentralized control
T2 - 2016 American Control Conference (ACC)
Y1 - 2016/08//
SP - 4323
EP - 4330
A1 - Weixuan Lin
A1 - Eilyan Bitar
KW - RM14-002
AB - We 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.
JF - 2016 American Control Conference (ACC)
PB - IEEE
CY - Boston, MA, USA
DO - 10.1109/ACC.2016.7525602
ER -
TY - CONF
T1 - Piecewise affine dispatch policies for economic dispatch under uncertainty
T2 - 2014 IEEE Power & Energy Society (PES) General Meeting
Y1 - 2014/07//
SP - 1
EP - 5
A1 - Munoz-Alvarez, Daniel
A1 - Eilyan Bitar
A1 - Lang Tong
A1 - Wang, Jianhui
KW - CERTS
KW - economic dispatch
KW - Power system modeling
KW - reliability and markets
KW - stochastic optimization
AB - Stochastic optimization has become one of the fundamental mathematical frameworks for modeling power systems with important sources of uncertainty in the demand and supply sides. In this framework, a main challenge is to find optimal dispatch policies and settlement schemes that support a market equilibrium. In this paper, the economic dispatch under linear network constraints and resource uncertainty is revisited. Piece-wise affine continuous dispatch policies and locational prices that support a market equilibrium using a two-settlement scheme are derived. We find that the ex-post locational prices are piecewise affine continuous functions of the system uncertainties.
JF - 2014 IEEE Power & Energy Society (PES) General Meeting
PB - IEEE
CY - National Harbor, MD, USA
DO - 10.1109/PESGM.2014.6939369
ER -