Online Feedback Optimization (OFO) controllers iteratively drive a plant to
an optimal operating point that satisfies input and output constraints, relying
solely on the input-output sensitivity as model information. This paper
introduces PRIME (PRoximal Iterative MarkEts), a novel OFO approach based on
proximal-point iterations. Unlike existing OFO solutions, PRIME admits a
market-based implementation, where self-interested actors are incentivized to
make choices that result in a safe and efficient operation, without
communicating private costs or constraints. Furthermore, PRIME can cope with
non-smooth objective functions, achieve fast convergence rates and rapid
constraint satisfaction, and reject measurement noise. We demonstrate PRIME on
an AC optimal power flow problem, obtaining an efficient real-time nonlinear
local marginal pricing scheme.

Cet article explore les excursions dans le temps et leurs implications.

Télécharger PDF: