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