Multi-objective distributed generation integration in radial distribution system using modified neural network algorithm

This paper introduces a new approach based on chaotic strategy and neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in radial distribution system (RDS). consists of determining locations sizes one or several generations (DGs) be inserted into RDS minimize multiple objectives while meeting set security limits. The robustness proposed method is demonstrated by applying it two different typical RDSs, namely IEEE 33-bus 69-bus. In this regard, simulations are performed for three DGs cases unity power factor (UPF) (OPF), considering single multi-objective optimization, minimizing total active losses improving voltage profile, deviation (VD) stability index (VSI). Compared its original version recently reported methods, CNNA solutions more competitive without increasing complexity optimization algorithm, especially when size problem dimension extended.