An empirical metaheuristic assessment for solving of multi-type distributed generation allocation problem

Abstract

This paper aims to map the use of algorithms with a metaheuristic approach to find optimal solutions for Distributed Generation (DG) placement. This paper surveyed six (6) algorithms tested on the same object, namely the IEEE 30 bus system with various types of DG. The algorithms are Genetic Algorithm (GA), Human Opinion Development (HOD), Particle Swarm Optimization (PSO), Artificial Bee Colony Algorithm (ABC), Adaptive Real Coded Biogeography-Based Optimization (ARCBBO), and Firefly Algorithm (FA). The review of each reference articles is done by comparing the optimal solutions obtained on the basis of an assessment of the reduction of power loss, while still interpreting the constraints of each function. This is because almost all the objective functions of the algorithm use these parameters. The solution offered by the FA provides significant results compared to other algorithms.

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