Welcome To UTPedia

We would like to introduce you, the new knowledge repository product called UTPedia. The UTP Electronic and Digital Intellectual Asset. It stores digitized version of thesis, dissertation, final year project reports and past year examination questions.

Browse content of UTPedia using Year, Subject, Department and Author and Search for required document using Searching facilities included in UTPedia. UTPedia with full text are accessible for all registered users, whereas only the physical information and metadata can be retrieved by public users. UTPedia collaborating and connecting peoples with university’s intellectual works from anywhere.

Disclaimer - Universiti Teknologi PETRONAS shall not be liable for any loss or damage caused by the usage of any information obtained from this web site.Best viewed using Mozilla Firefox 3 or IE 7 with resolution 1024 x 768.

Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm

Mohd Tholaat, Muhammad Ali Husaini (2015) Multi-Objective Optimization of Solar Powered Irrigation System by Using Genetic Algorithm. IRC, Universiti Teknologi PETRONAS. (Unpublished)

[img] PDF
Download (801Kb)

Abstract

Irrigation system is synonym with agriculture. Conventional way of supplying source of energy to work the water pumping system is through fuel combustion such as diesel. Nowadays fuel combustion is not an attractive and feasible approach in a long run due to hiking fuel price and it is also not environmentally friendly which it may lead to pollution. The development of renewable energy such as solar energy as an external heat source rather be more attractive. However, this complex system needs to be optimized by using suitable metaheuristic technique in order to make the design to be economically and practically efficient. Thus, Genetic Algorithm is applied to solve multiple objective solar-irrigation system optimization. It is identified that the best setting should be input to get an optimal solution. Initial range of [1; 2] and crossover fraction of 1.0 have majorly contributed to the optimal search parameters. After some tuning to get the best setting, the simulation shows that the fitness function of 3 objectives resulted with 17.4303 kW power output, 15.2355% efficiency and $143,533.10 fiscal savings. This set of optimal solution is not as closed as other technique to the desired design objectives. Genetic Algorithm is a common technique and easy to work with but it has yet to be the best metaheuristic technique for this engineering problem due to some drawbacks

Item Type: Final Year Project
Academic Subject : Academic Department - Chemical Engineering - Separation Process
Subject: T Technology > TP Chemical technology
Divisions: Engineering > Chemical
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 22 Feb 2016 10:25
Last Modified: 25 Jan 2017 09:35
URI: http://utpedia.utp.edu.my/id/eprint/16270

Actions (login required)

View Item View Item

Document Downloads

More statistics for this item...