Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Analysing design parameters of hydroelectric power plant projects to develop cost decision models by using regresion and neural network tools
Download
index.pdf
Date
2010
Author
Şahin, Hacı Bayram
Metadata
Show full item record
Item Usage Stats
240
views
88
downloads
Cite This
Energy is increasingly becoming more important in today’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.
Subject Keywords
Civil engineering.
URI
http://etd.lib.metu.edu.tr/upload/3/12611462/index.pdf
https://hdl.handle.net/11511/19181
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Biogas generation by two-phase anaerobic digestion of organic fraction of municipal solid waste
Dogan, Eylem; Demirer, Göksel Niyazi (2012-11-01)
The organic fraction of municipal solid waste can be a significant energy source for renewable energy generation. The total production of municipal solid waste in Turkey was 25 x 10(6) tones per year. Anaerobic digestion (AD) process may be a solution to the problems of energy demand and waste management since it provides biomethanation along with waste stabilization. AD can be operated in single or two phase configurations. Two-phase processes have some advantages over one phase systems in terms of selecti...
Development of an expert system for the quantification of fault rates in traffic accidents
Cangul, Eren; Birgönül, Mustafa Talat; Department of Civil Engineering (2010)
Traffic accidents which damage the safety of human beings are one of the most important problems due to their material losses and effects to human health. Although continuous improvements are made by the governments; losses of traffic accidents are still a significant issue all over the world. The usual studies realized so far are generally related with the accident prevention models. However, there has not been much research done concerning the situation after the traffic accidents happen. After occurrence...
Evaluating the use of satellite-based precipitation estimates for discharge estimation in ungauged basins
Soytekin, Arzu; Akyürek, Sevda Zuhal; Department of Civil Engineering (2010)
For the process of social and economic development, hydropower energy has an important role such as being renewable, clean, and having less impact on the environment. In decision of the hydropower potential of a study area, the preliminary condition is the availability of the gages in the area. However, in Turkey, the gages in working order are limited and getting decreased in recent years. Therefore, the satellite based precipitation estimates has been gaining importance to predict runoff for ungauged basi...
An analysis on the utilization of energy and exergy in Turkey
Acar, Berkan; Yamalı, Cemil; Department of Mechanical Engineering (2008)
Today, energy has become one of the most indispensable necessities in the world. Most of the wars and the disputes between the countries have been arising because of the increasing scarcity of energy resources. Therefore, like most country, Turkey has also started to develop new energy policies for more efficient production and utilization of energy. In order to help the understanding of more efficient energy utilization, so far there have been some researches made about energy and exergy (available energy)...
Energy dissipation by vertically placed screens
Bozkuş, Zafer; GER, A. Metin (Canadian Science Publishing, 2007-04-01)
Screens can be utilized efficiently for dissipating energy of water. In this study, water flowing beneath a gate is used to simulate the flow downstream of a small hydraulic structure, and vertically placed screens are used as an alternative tool for energy dissipation. Investigations are conducted using a series of experiments. The porosity, thickness, and location of the screens are the major parameters together with the Froude number of the upstream flow. The experiments cover a range of supercritical Fr...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. B. Şahin, “Analysing design parameters of hydroelectric power plant projects to develop cost decision models by using regresion and neural network tools,” M.S. - Master of Science, Middle East Technical University, 2010.