  The development of smart grids has effectively transformed the traditional
grid system. This promises numerous advantages for economic values and
autonomous control of energy sources. In smart grids development, there are
various objectives such as voltage stability, minimized power loss, minimized
economic cost and voltage profile improvement. Thus, researchers have
investigated several approaches based on meta-heuristic optimization algorithms
for the optimal location and sizing of electrical units in a distribution
system. Meta-heuristic algorithms have been applied to solve different problems
in power systems and they have been successfully used in distribution systems.
This paper presents a comprehensive review on existing methods for the optimal
location and sizing of electrical units in distribution networks while
considering the improvement of major objective functions. Techniques such as
voltage stability index, power loss index, and loss sensitivity factors have
been implemented alongside the meta-heuristic optimization algorithms to reduce
the search space of solutions for objective functions. However, these
techniques can cause a loss of optimality. Another perceived problem is the
inappropriate handling of multiple objectives, which can also affect the
optimality of results. Hence, a recent method such as Pareto fronts generation
has been developed to produce non-dominating solutions. This review shows a
need for more research on (i) the effective handling of multiple objective
functions, (ii) more efficient meta-heuristic optimization algorithms and/or
(iii) better supporting techniques.
