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

• Published in: International transactions on electrical energy systems Vol. 31; no. 12
• Main Authors: Ayazi, Sajjad, Askarzadeh, Alireza
• Format: Journal Article
• Language: English
• Published: Hoboken John Wiley & Sons, Inc 01.12.2021
• Subjects: Combinatorial analysis; combinatorial optimization; differential crow search algorithm; distribution network planning; Electric power distribution; Electric power loss; feeder routing; Objective function; Optimization techniques; Particle swarm optimization; Search algorithms
• ISSN: 2050-7038; 2050-7038
• DOI: 10.1002/2050-7038.13196

Feeder routing is one of the most important and challenging problems of distribution network planning. Optimal feeder routing is a complex combinatorial optimization problem, which needs a superior optimization technique to be effectively solved. In such problem, minimization of investment cost and power losses subject to distribution network limitations is the main issue. In this article, differential crow search algorithm (CSAdif) is proposed to effectively solve feeder routing problem. CSAdif utilizes the strength of multiple high‐quality solutions to determine search direction. Over a relatively large real system (SKED 61‐bus distribution network), simulation results show superior performance of the proposed approach in comparison with original CSA and different variants of particle swarm optimization (PSO). The value of objective function is obtained 43 780 $ where the portion of investment and losses costs is 28 042 and 15 738 $, respectively. Moreover, in the optimal configuration, power losses and minimum voltage value are 42.80 kW and 0.982 p.u., respectively. Optimal feeder routing is a complex combinatorial optimization problem, which needs a superior optimization technique to be effectively solved. Differential crow search algorithm (CSAdif) is proposed to effectively solve feeder routing problem. CSAdif utilizes the strength of multiple high‐quality solutions to determine search direction.