  We consider the problem of distributed secondary frequency regulation in
power networks such that stability and an optimal power allocation are
attained. This is a problem that has been widely studied in the literature, and
two main control schemes have been proposed, usually referred to as
'primal-dual' and 'distributed averaging proportional-integral (DAPI)'
respectively. However, each has its limitations, with the former requiring
knowledge of uncontrollable demand, which can be difficult to obtain in real
time, and with the existing literature on the latter being based on static
models for generation and demand. We propose a novel control scheme that
overcomes these issues by making use of generation measurements in the control
policy. In particular, our analysis allows distributed stability and optimality
guarantees to be deduced with practical measurement requirements and permits a
broad range of linear generation dynamics, that can be of higher order, to be
incorporated in the power network. We show how the controller parameters can be
selected in a computationally efficient way by solving appropriate linear
matrix inequalities (LMIs). Furthermore, we demonstrate how the proposed
analysis applies to several examples of turbine governor models. The
practicality of our analysis is demonstrated with simulations on the Northeast
Power Coordinating Council (NPCC) 140-bus system that verify that our proposed
controller achieves convergence to the nominal frequency and an economically
optimal power allocation.
