Optimal Selection Of Renewable Energy Installation Site In Remote Areas Using Segmentation And Regional Technique: A Case Study Of Sarawak, Malaysia

Khamis, Aziah and Mohd Yosliza, Nur Amira Haziqah and Azmi, Aimie Nazmin and Khatib, Tamer T.N. (2020) Optimal Selection Of Renewable Energy Installation Site In Remote Areas Using Segmentation And Regional Technique: A Case Study Of Sarawak, Malaysia. Sustainable Energy Technologies and Assessments, 42. pp. 1-8. ISSN 2213-1388

[img] Text
1-S2.0-S2213138820312856-MAIN.PDF
Restricted to Registered users only

Download (3MB)

Abstract

Electricity access in many remote areas in Sarawak, Malaysia is very little due to some limitations including the complicated geographical factors and high costs. In fact, there are about 1623 locations in Sarawak without electricity, whereas 420 locations (small settlements) can be only electrified using isolated renewable energy microgrid. However, it is impossible to install individual systems for each location. Thus, the optimal clustering of these locations and the selection of sites that are located in the centers of these clusters is necessary. Therefore, in this research, image segmentation and regional technique are used to analyze the map of remote electrification in Sarawak. The image segmentation which includes color thresholding, circular hough transform, and K-means technique is used in this research to identify the optimal installation site. HOMER software is then used to optimize the proposed renewable energy systems. Results show that nine locations out of 420 locations are optimum locations for the installation of renewable power systems. These nine locations are the centers of the obtained nine clusters of communities and small villages. Finally, it is found that most of the recommended combinations are hybrid renewable energy systems, where photovoltaic and hydropower systems combination is found the best hybrid system for the rural areas in Sarawak.

Item Type: Article
Uncontrolled Keywords: HOMER, Hybrid renewable energy, Image segmentation, Site selection
Divisions: Faculty of Electrical Engineering
Depositing User: Sabariah Ismail
Date Deposited: 01 Mar 2021 16:18
Last Modified: 01 Mar 2021 16:18
URI: http://eprints.utem.edu.my/id/eprint/24848
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item