Energy is increasingly becoming more important in today&rsquo / s world. Ascending of
energy consumption due to development of technology and dense population of
earth causes greenhouse effect. One of the most valuable energy sources is
hydro energy. Because of limited energy sources and excessive energy usage,
cost of energy is rising. There are many ways to generate electricity. Among the
electricity generation units, hydroelectric power plants are very important, since
they are renewable energy sources and they have no fuel cost. Electricity is one
of the most expensive input in production. Every hydro energy potential should
be considered when making investment on this hydro energy potential. To
decide whether a hydroelectric power plant investment is feasible or not, project
cost and amount of electricity generation of the investment should be precisely
estimated. This study is about cost estimation of hydroelectric power plant
projects. Many design parameters and complexity of construction affect the cost of hydroelectric power plant projects. In this thesis fifty four hydroelectric power
plant projects are analyzed. The data set is analyzed by using regression analysis
and artificial neural network tools. As a result, two cost estimation models have
been developed to determine the hydroelectric power plant project cost in early
stage of the project.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12611462/index.pdf |
| Date | 01 December 2009 |
| Creators | Sahin, Haci Bayram |
| Contributors | Gunduz, Murat |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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