Electric distribution network reconfiguration for power loss reduction based on runner root algorithm

Abstract

This paper proposes a method for solving the distribution network reconfiguration (NR) problem based on runner root algorithm (RRA) for reducing active power loss. The RRA is a recent developed metaheuristic algorithm inspired from runners and roots of plants to search water and minerals. RRA is equipped with four tools for searching the optimal solution. In which, the random jumps and the restart of population are used for exploring and the elite selection and random jumps around the current best solution are used for exploiting. The effectiveness of the RRA is evaluated on the 16 and 69-node system. The obtained results are compared with particle swarm optimization and other methods. The numerical results show that the RRA is the potential method for the NR problem.

An effective network reconfiguration approach of radial distribution system for loss minimization and voltage profile improvement

“…Since the branch current is given in (1), so one can substitute it in (2), then the obtained equation is [18],…”

Optimal distribution network configuration using improved backtracking search algorithm

“…The pseudo-code of IBSA for solving the network reconfiguration problem is shown in Figure 1. Assign the starting solution to the current population by using 7Validate the adaptive function of each solution is validated by (4) Determine the best so-far solution ( ) with the best adaptive function value ( ) Generate the historical population by using (5) and (6) Set the current generation equal to zero While the current generation < do // Step 3: Redefine the historical population Redefine the historical population by using (8) Permute the historical population by using (9) // Step 4: Generate new population Generate new population by using (11) Check and correct the bound of new population by using (13) // Step 5: update the population for next generation Modify the generated population by using (6) Validate the adaptive function of each solution is validated by (4) Update the current population by using (14) and (15) // Step 6: update the best so-far solution Update the best so-far solution by using (16) and (17) Increase the current generation End while…”

“…However, network reconfiguration is a nonlinear and discrete problem that needs to have effective solving methods. For finding optimal network configuration, there are a lot of solving methods consisting of methods based on mathematical approaches [1][2][3][4] methods based on experience of operating the power system [5][6][7] and methods developed from metaheuristic algorithms [8][9][10][11][12][13][14][15][16]. By using the methods based on mathematical approaches, description of network reconfiguration problem and solving process are complicated because the network reconfiguration problem has to be linearized.…”

A Novel Metaheuristic Method for Multi-Goal Electric Distribution Network Reconfiguration

“…In [1], power loss reduction is considered as the objective function of the ENRP and mixed PSO (MPSO) has been proposed for searching the optimal network configuration. In [2], the ENRP for power loss reduction problem has been successful solved by the runner root algorithm. In [3], a method based on backtracking search algorithm has been used to search the network configuration that causes minimum power loss.…”