Abstract

This paper presents a new hybrid multi-objective optimization algorithm for optimal placement and sizing of Renewable Energy
Generations (here, photovoltaic system) in distribution networks. For this purpose, a multi-objective non-dominated sorting genetic
algorithm (NSGA II) is implemented to offer variety sets of solutions as a two/three-dimensional Pareto optimal set. To find the final
solution, a fuzzy decision-making tool (FDMT) is proposed to extend the notion of Pareto method and obtain the optimal solution from
the Pareto optimal set. In this study, three objectives are defined: (a) the minimization of distribution network power losses; (b)
minimization of comprehensive annual cost including capital, operation, and maintenance costs; (c) minimization of stability (JBSI
, JLSI
)
and security (JVSI
,
 JTCSI) indices. A robust direct power flow method employing BIBC and BCBV matrices along with a simple matrix
calculation is used as a fast and reliable approach for the load flow calculation in the distribution system. The combination of PV(s)
along with a capacitor is investigated in order to provide for flexible planning. The performance and effectiveness of the proposed
method are tested by considering different case studies on a 33-bus, 69-bus, and 228-bus real radial distribution systems and the results
are presented. These results are compared with other methods and it is shown that the proposed method exhibits higher capability,
efficiency, and flexibility in improving the distribution system characteristics.