The control and operation of an electric power system is based on the
ability to determine the state of the system in real time. State
estimation (SE) has been introduced in the 1960s to achieve this
objective. The initial implementation was based on single-phase
measurements and a power system model that was assumed to operate under
single-frequency, balanced conditions, and a symmetric system model. These
assumptions are still prevalent today. The single-frequency, balanced, and
symmetric system assumptions have simplified the implementation but have
generated practical problems. The experience is that the SE problem does
not have 100% performance; that is, there are cases and time periods for
which the SE algorithm will not converge. There are practical and
theoretical reasons for this and they are explained in the paper. Recent
mergers and mandated regional transmission organizations (RTOs) as well as
recent announcements for the formation of mega-RTOs will result in the
application of the SE in systems of unprecedented size. We believe that
these practical and theoretical issues will become of greater importance.
There are scientists who believe that the SE problem is scalable, meaning
that it will work for the mega-RTOs the same way that it performs now for
medium–large systems. There are scientists who believe that this is
not true. The fact is that no one has investigated the problem, let alone
performed numerical experiments to prove or disprove any claims. This
paper identifies a number of issues relative to the SE of mega-RTOs and
provides some preliminary results from numerical experiments for the
relation between the SE algorithm performance and the power system
size.