A hybrid evolutionary algorithm for distribution feeder reconfiguration

Abstract

This paper presents a new method to reduce the distribution system loss by feeder reconfiguration. This new method combines self-adaptive particle swarm optimization (SAPSO) with shuffled frog-leaping algorithm (SFLA) in an attempt to find the global optimal solutions for the distribution feeder reconfiguration (DFR). In PSO algorithm, appropriate adjustment of the parameters is cumbersome and usually requires a lot of time and effort. Thus, a self-adaptive framework is proposed to improve the robustness of PSO. In SAPSO the learning factors of PSO coevolve with the particles. SFLA is combined with the SAPSO algorithm to improve its performance. The proposed algorithm is tested on two distribution test networks. The results of simulation show that the proposed algorithm is very powerful and guarantees to obtain the global optimization in minimum time.self-adaptive particle swarm optimization (SAPSO), discrete particle swarm optimization (DPSO), binary particle swarm optimization (BPSO), shuffled frog-leaping algorithm (SFLA), evolutionary algorithms (EA), distribution feeder reconfiguration (DFR) Citation:Niknam T, Azad Farsani E. A hybrid evolutionary algorithm for distribution feeder reconfiguration. Sci China Tech Sci, 2010, 53: 950−959,

Two-Phases Learning Shuffled Frog Leaping Algorithm

“…However, from the above analyses, TLSFLA is not suitable for all kinds of function comparing with ABC and ISPO, for example, 5 f , 6 f , 8 f and 13 f . It suggests that the presented approach might not be enough to prevent the search falling into local optimum.…”

“…SFLA, basically combines the benefits of the mimetic algorithm (MA) [2] based on genetic evolution as well as particle swarm optimization(PSO) based the social behavior [3], has many advantages [4] which are simple structure, fast evolution velocity, a few parameters and easy implementation. it has been applied in these fields successfully, such as water Distribution [1], distribution feeder reconfiguration [5], assembly line sequencing problem [6], function optimization [7], Wireless Sensor Network Coverage Optimization [8], Wind Power Integrated System [9].…”

Segmentation and Edge Detection Based on Modified ant Colony Optimization for Iris Image Processing

“…Ants are soon fascinated to this path and the best path from the nest to the food source is established as shown in Figure 1. Furthermore some of the ants search in habitat to find new food sources [15][16][17].…”

An efficient multi-objective modified shuffled frog leaping algorithm for distribution feeder reconfiguration problem

“…Das proposed a fuzzy multi-objective approach to solve the network reconfiguration problem [9]. Niknam et al [10][11][12] proposed three approach based on hybrid evolutionary algorithm (EA) for single-objective DFR problem. Olamaei et al proposed a cost-based compensation methodology for distribution feeder reconfiguration considering distributed generators [13,14].…”

“…Olamaei et al proposed a cost-based compensation methodology for distribution feeder reconfiguration considering distributed generators [13,14]. Niknam presented an approach based on norm2 for MDFR problem [15,16]. The author utilized hybrid algorithms based on the combination of particle swarm optimization and ant colony optimization (PSO-ACO) [16], discrete particle swarm, and HBMO (DPSO-HBMO) [17] to solve the DFR problem.…”