6533b7d7fe1ef96bd12679b9

RESEARCH PRODUCT

Dynamic Demand and Mean-Field Games

subject

description

Within the realm of smart buildings and smart cities,\ud dynamic response management is playing an ever-increasing\ud role thus attracting the attention of scientists from different\ud disciplines. Dynamic demand response management involves a\ud set of operations aiming at decentralizing the control of loads\ud in large and complex power networks. Each single appliance\ud is fully responsive and readjusts its energy demand to the\ud overall network load. A main issue is related to mains frequency\ud oscillations resulting from an unbalance between supply and\ud demand. In a nutshell, this paper contributes to the topic by\ud equipping each signal consumer with strategic insight. In particular,\ud we highlight three main contributions and a few other minor\ud contributions. First, we design a mean-field game for a population\ud of thermostatically controlled loads (TCLs), study the mean-field\ud equilibrium for the deterministic mean-field game and investigate\ud on asymptotic stability for the microscopic dynamics. Second, we\ud extend the analysis and design to uncertain models which involve\ud both stochastic or deterministic disturbances. This leads to robust\ud mean-field equilibrium strategies guaranteeing stochastic and\ud worst-case stability, respectively. Minor contributions involve the\ud use of stochastic control strategies rather than deterministic, and\ud some numerical studies illustrating the efficacy of the proposed\ud strategies.