  Conventional optimal power flow (OPF) solvers assume full observability of
the involved system states. However, in practice, there is a lack of reliable
system monitoring devices in the distribution networks. To close the gap
between the theoretic algorithm design and practical implementation, this work
proposes to solve the OPF problems based on the state estimation (SE) feedback
for the distribution networks where only a part of the involved system states
are physically measured. The SE feedback increases the observability of the
under-measured system and provides more accurate system states monitoring when
the measurements are noisy. We analytically investigate the convergence of the
proposed algorithm. The numerical results demonstrate that the proposed
approach is more robust to large pseudo measurement variability and inherent
sensor noise in comparison to the other frameworks without SE feedback.
