Enhanced Sine–Cosine Algorithm for Optimal Planning of Distribution Network by Incorporating Network Reconfiguration and Distributed Generation

One of the important directions of the current research trend in distribution network planning in the prevailing smart grid scenario, is to explore various possibilities to enhance the performance of these networks without expanding the existing infrastructure. This paper proposes an enhanced sine–cosine algorithm (ESCA) to obtain an optimally planned system by simultaneous incorporation of network reconfiguration (NR) and DG allocation. In the proposed algorithm, the SCA is enhanced with neighborhood search strategy and self-adapting levy mutation strategy to ensure proper balance between exploration and exploitation during different reconfiguration phases. A multi-objective function is formulated considering the reduction of total real power loss and annual operation costs with suitable weights without violating the system operating constraints. The proposed algorithm is successfully experimented on 33- and 69-bus distribution system with four distinct scenarios of NR and DG allocation, and its performance assessment is based on technical (total system active power loss index, overall voltage stability index and voltage profile improvement index), economic (total system operation cost index) and reliability (expected energy not supplied index) indices. As the computation of reliability index adds complexity to the problem, a graph theory-based algorithm is proposed for its accurate calculation. The obtained results showed the effectiveness of ESCA for solving simultaneous NR and DG allocation problem over other competitive algorithms, and its robustness is confirmed through a detailed statistical analysis such as plotting of box plots, normality checking and two nonparametric tests, namely Friedman ANOVA and Wilcoxon signed rank tests.