  Distributed state estimation (DSE) is considered as a more robust and
reliable alternative for centralized state estimation (CSE) in power system.
Especially, taking into account the future power grid, so called smart grid in
which bi-directional transfer of energy and information happens, and renewable
energy sources with huge indeterminacy are applied more than before. Combining
the mentioned features and complexity of the power network, there is a high
probability that CSE face problems such as communication bottleneck or
security/reliability issues. So, DSE has the potential to be considered as a
solution to solve the mentioned issues. In this paper, first, a modified
convergence criterion is proposed and has been tested for different approaches
of DSE problem, considering the most important factors such as iteration
number, convergence rate, and data needed to be transferred to/from each area.
Then, an optimal partitioning technique has been implemented for clustering the
system into different areas. Besides the detailed analysis and comparison of
recent DSE methods, the proposed partitioning method's effectiveness has been
shown in this paper.
