Optimization of electrical wiring design in buildings using particle swarm optimization and genetic algorithm / Tuan Ahmad Fauzi Tuan Abdullah

In Malaysia, the number of population in the cities is increasing due to urbanization and job opportunities. As a result, the number of high rise building is also increasing. Hence, electrical system is becoming crucial in the construction of high rise building so that the building could be occupied...

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Bibliographic Details
Main Author: Tuan Ahmad Fauzi, Tuan Abdullah
Format: Thesis
Published: 2017
Subjects:
Online Access:http://studentsrepo.um.edu.my/8543/
http://studentsrepo.um.edu.my/8543/4/KMA150009.pdf
Description
Summary:In Malaysia, the number of population in the cities is increasing due to urbanization and job opportunities. As a result, the number of high rise building is also increasing. Hence, electrical system is becoming crucial in the construction of high rise building so that the building could be occupied safely and comfortably by tenants or residences. Commonly, electrical system is designed based on the customers’ requirements and it must comply according to certain requirements and regulation from authorities or standard bodies. The electrical wiring system design includes sizing of cables and bus ducts, customers’ load and placement of load, cables and bus ducts. Therefore, these parameters have to be emphasized on the planning stage. In this project, the main objective is to optimize the electrical distribution system design in buildings using optimization methods, which are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The main reasons of using these optimization methods is to propose a minimum total cost and lowest voltage drop of electrical system design in buildings.Comparison between the optimisation methods and without using optimisation methods show that the total cost and total voltage drop are lower when using optimisation methods. Comparison between the results using PSO and GA shows that both methods yield the same total cost and total voltage drop but GA yields consistent results compared to PSO. Therefore, GA is more suitable than PSO in finding the lowest total voltage drop and total cost when designing an electrical system in a building.