Recent Trends of the Most Used Metaheuristic Techniques for Distribution Network Reconfiguration

Abstract

Distribution network reconfiguration (DNR) continues to be a good option to reduce technical losses in a distribution power grid. However, this non-linear combinatorial problem is not easy to assess by exact methods when solving for large distribution networks, which requires large computational times. For solving this type of problem, some researchers prefer to use metaheuristic techniques due to convergence speed, near-optimal solutions, and simple programming. Some literature reviews specialize in topics concerning the optimization of power network reconfiguration and try to cover most techniques. Nevertheless, this does not allow detailing properly the use of each technique, which is important to identify the trend. The contributions of this paper are three-fold. First, it presents the objective functions and constraints used in DNR with the most used metaheuristics. Second, it reviews the most important techniques such as particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), ant colony optimization (ACO), immune algorithms (IA), and tabu search (TS). Finally, this paper presents the trend of each technique from 2011 to 2016. This paper will be useful for researchers interested in knowing the advances of recent approaches in these metaheuristics applied to DNR in order to continue developing new best algorithms and improving solutions for the topic.

Distribution Network Reconfiguration with Large Number of Switches Solved by a Modified Binary Bat Algorithm and Improved Seed Population

“…As this algorithm was prepared in MATLAB © , the function permpos was used for obtaining all the permutations calculated from Eq. (16). Every configuration attained from this step fulfils with Eqs.…”

“…For a single bat, a configuration is selected randomly from the binary matrix calculated in Eq. (16). For real purposes, the number of bats is set and a matrix for all initial bat configurations is described for each bat.…”

“…When a configuration does not comply with this constraint, it is randomly changed for another combination from the matrix binary obtained in Eq. (16). Once a new position is obtained, it must be evaluated in the same manner.…”

“…Most researchers have used metaheuristic techniques to reduce the time evaluation by finding good solutions and redirecting the search process to the best-found solutions [14]; however, these algorithms have some convergence problems and the solutions are not always obtained near the optimal [15]. A detailed state-of-the-art in recent trends concerning reconfiguration and most used metaheuristic techniques is in [16].…”

A modified backward/forward sweep-based method for reconfiguration of unbalanced distribution networks

“…Distribution networks are unbalanced systems in which loads are not precisely balanced through the network [1]- [3]. This feature rejects conventional balanced power flow methods, such as Newton-Raphson and Gauss-Seidel, to converge in order to find a solution for the non-linear power flow problem [4]- [6].…”