Abstract:
This paper presents efficient, nature inspired ant lion optimization (ALO) and multiverse
optimization (MVO) techniques for the optimal allocation of DGs in Active distribution
networks (ADNs). The main objective is to improve techno-economic and
environmental attributes while satisfying system’s constraints. In comparison to the
ALO method, the MVO algorithm has the drawback of requiring a large number of iterations
to reach an optimal solution. Various MCDM approaches are used in this study
to determine the optimal trade-off among the available solutions. The effectiveness of
the suggested ALO approach has been confirmed on the IEEE-33 and 69 bus ADNs, the
obtained results were validated by comparing them to other methods in the literature.
The test system results indicate that the developed algorithms produces the highest Loss
reduction in the IEEE-33 and 69 bus systems as 94.43% and 97.16%, respectively, and
the maximum VSI is 0.9805 p.u and 0.9937 p.u, respectively; however, the minimum
VD and annual energy loss cost for the given test systems is 0.00019 p.u and $3353.3
which shows that the suggested method can produce higher quality results as compared
to other methods presented in literature. As a result, the proposed ALO could be very
effective, efficient and appealing solution to the OADG problem.
