Optimal Feeder Routing and DG Placement Using Kruskal’s Algorithm

Abstract

In this paper, the optimal feeder routing along with optimal distributed generator placement is formulated as an optimization problem. In this problem, the total cost of capital recovery, supply interruption and energy losses are minimized. Also, line loading capacity and bus voltage constraints are applied. By proposing a novel method to code the solutions of the optimization problem with the facilitation obtained from the utilization of the Kruskal's algorithm, it is guaranteed that graphs of all solutions would always be spanning trees. The main result of the implementation of this method within meta-heuristic algorithms is to limit the search space to radial networks leading to snap quicker answers with higher degree of optimality. A distribution network with a 24 load points and 42 candidate branches is used as a baseline to indicate the effectiveness of the proposed method which was tested using three meta-heuristic algorithms including genetic algorithm, particle swarm optimization and simulated annealing.

Finding optimal path of feeder routing problem in power distribution network by an efficient and new methodology

“…In References 19,20, minimum spanning tree (MST) has been proposed to solve optimal feeder routing problem in distribution network. In Reference 21, feeder routing problem has been solved by Kruskal's algorithm. Optimal allocation of distributed generations (DGs) has been also considered in the problem.…”

Reliability Evaluation of Direct Current Distribution System for Intelligent Buildings Based on Big Data Analysis

“…Compared with the traditional alternating current (AC) distribution mode, the DC distribution mode makes electric energy controllable, and facilitates the access of electronic devices, and distributed power sources, such as wind turbines and photovoltaic (PV) devices. The DC distribution system has great advantages in energy conservation and supply efficiency [8][9][10].…”