Modeling of industrial sector in Singapore

• Main Author: Koh, Soon Peng.
• Other Authors: Toh Kok Chuan
• Format: Final Year Project
• Language: English
• Published: 2009
• Subjects: DRNTU::Engineering::Industrial engineering
• Online Access: http://hdl.handle.net/10356/16874
• Institution: Nanyang Technological University

With the world’s conventional energy sources dwindling over the years and the mounting threat of environmental consequences caused by the ever increasing use of these energy sources, it is in the interest of every country to plan her energy needs for the future. Singapore, too, is vulnerable to this energy threat and consequences. Being a country that has enjoyed fast growth over the past few decades, Singapore inevitably has a keen interest to plan for her energy needs to sustain her growth. At the forefront driving Singapore’s economic growth is her industrial sector, which has been one of the main pillars of the country. The ability to model the industrial sector of Singapore would provide great potential for policy planning. In this project, a model using the Markal framework is developed on Singapore’s industrial sector, over a span of thirty years, from year 2000 to 2030. Markal allows for the optimization of the model created, by obtaining the lowest energy system cost. As specific data regarding industrial technology remains highly guarded in this field, assumptions have been made during the creation of the model. From the results generated by Markal, it is seen that second generation technology are the preferred choice due to the improvement in efficiency. In areas where competing base technology are present, such as lightings and HVAC, energy saving light bulbs and second generation split unit are selected respectively as the most cost effective technology. In conclusion, although the model created does not fully reflect the entire Singapore energy situation, it possesses the ability of portraying Singapore’s industrial sector into the near future. By acquiring more accurate information, the accuracy of this model would be greatly enhanced.