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Enerji ve elektrik yoğunluklarındaki eğilimlerin gelişmişlik ekseninde incelenmesi

Analysis of energy and electricity intensity trends in the frame of development basis

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  1. Tez No: 397838
  2. Yazar: TURHAN KARAYEL
  3. Danışmanlar: DOÇ. DR. NAZİF HÜLAGÜ SOHTAOĞLU
  4. Tez Türü: Yüksek Lisans
  5. Konular: Enerji, Energy
  6. Anahtar Kelimeler: Belirtilmemiş.
  7. Yıl: 2015
  8. Dil: Türkçe
  9. Üniversite: İstanbul Teknik Üniversitesi
  10. Enstitü: Fen Bilimleri Enstitüsü
  11. Ana Bilim Dalı: Elektrik Mühendisliği Ana Bilim Dalı
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: 75

Özet

Geçmişten günümüze kadar yapılan çalışmalarda, kişi başına düşen gelir düzeylerindeki dengesizliklerin ortadan kalkıp, kalkmayacağı konusu üzerine bir çok araştırma yapılmıştır. Sonuç olarak, yakınsama hipotezi ortaya çıkmıştır. Yakınsama hipotezi; yoksul ülke ya da bölgelerin zamanla varsıl ülke ya da bölgelerin gelişmişlik düzeyine ulaşacağını ve dolayısıyla da gelir seviyeleri bakımından da birbirlerine yaklaşacağını ifade etmektedir. Bu hipotezin temelini gelişmiş olan ülke veya bölgelerden, az gelişmiş ülke ya da bölgelere bir sermaye akışı beklentisi oluşturur. Yakınsama hipotezinin ekonomik büyüme konusu ekseninde kullanılmasının ardından, enerji ile ilgili konularda da bu kavram ile çalışmalar yapılmıştır. Beta yakınsaması, sigma yakınsaması ve gama yakınsaması gibi kavramlar kullanılmış, enerji yoğunluğu ve elektrik yoğunluğu ile ilgili olarak ülkeler arasındaki yakınsama durumları incelenmiştir. Bu çalışmada, yakınsama kavramının tarihsel gelişimi hakkında bilgi verilmiş, beta yakınsaması, sigma yakınsaması ve gama yakınsaması kavramları açıklanmıştır. Ardından, toplam birincil enerji arzı (TBEA), toplam elektrik enerjisi tüketimi (TEET), satın alma gücü paritesine göre hesaplanan gayri safi yurt içi hasıla (GSYH) ve nüfus (NFS) büyüklükleri ile tanımlanan veri kümesi kapsamında, temel büyüklükler ile bunların kişi başına düşen değerleri gözetilerek enerji yoğunluğu (ENYO) ve elektrik yoğunluğu (ELYO) eğilimleri irdelenmiştir. Seçilen ülke gruplarındaki enerji yoğunluğu ve elektrik yoğunluğu yakınsamaları incelenirken, sigma yakınsamasının histogramlarla saptanan ölçümü kullanılmıştır. Enerji ve elektrik yoğunluklarındaki gelişmelerin, gelişmişlik ekseninde incelenmesi ile birlikte Türkiye değerlendirmesi de yapılarak dönemler itibariyle ulaşılan sonuçların karşılaştırılmalı halde sunulması amaçlanmıştır.

Özet (Çeviri)

Since ancient times people use primary energy supplies, oil, coal, natural gas etc, for their needs. In the next period, after urban life and technology are improved, environment and pollution begins to get more important. Depending on these two basic reasons, secondary energy supplies are started to be used in the market. Secondary energy supplies consist of using primary energy supplies. An example of secondary energy supplies is electricity, which is easy use and clean sort of energy. It is used largely depending on its superior specifications although cannot be stored effectively except small quantities. It can also be transmitted easily from manufacturing places to regions to be used and it can be easily controlled when it is needed. Electricity consumption per capita is a very good development indicator due to connection of environment and technology. In these days, because of some reasons such as industrialization and fast population increase, energy demand is getting much more than usual. While demand is increasing, to meet this demand is getting more difficult due to limited reserves in time. Depending on such conditions, it is needed and obligation that energy must be used effectively and efficiently. Energy efficiency means to decrease supply to be used to a minimum level and get maximum output. So, by using the same supply, it may be got more output than before. One of important indicator for energy efficiency is energy intensity concept. Energy intensity can be identified as energy use per gross domestic product (GDP) and represented by TPES/GDP ratio. TPES is given by total primary energy supply. Energy Intensity is an important indicator that represents using energy whether efficiently or not. It is said that if energy intensity of a country is lower, then this country has a developed economy. Also, it is a very important and useful subject for politics makers to forecast how energy consumption increases before facing significant changes in economy management system and economic structure. Since 1973, industrialized countries focus and take into account of energy efficiency. These countries, due to oil crises in 70's, get improve their energy efficiency politics and enforce them in all sectors. Because of energy politics contribution, energy intensity decreases last year's in these developed countries. There are a lot of studies whether unbalanced levels in gross domestic product per capita to be solved and balanced or not until recent days. As a result, convergence hypothesis appears regarding this issue. Convergence hypothesis states that poor countries or regions' level are going to reach rich countries or regions' level of development in time and they converge each other according to their GDP per capita. The basic of this hypothesis consists of an expectation due to a capital transition from developed countries or regions to developing countries or regions. After convergence hypothesis is used in economic growth literature, it is also used in energy matters and some studies are realized in energy sector. Energy and electricity intensity may be submitted as an example. Depending on these studies, some concepts such as beta convergence, sigma convergence and gamma convergence by borrowing from economic growth literature are used for energy intensity and electricity intensity of countries to examine whether any convergence or not in between them. In my study, convergence concept is examined and given some information regarding its improving in history in time. Beta, sigma and gamma convergence are explained and submitted information about their applications in energy and electricity intensity. Then, I separate countries according to their developing of developed position and examine OECD, Non-OECD, world total countries nad Turkey's values. After that, total primary supply (TPES), total electricity consumption (EC), gross domestic product according to purchasing power parity (GDP-PPP), population (POP), energy intensity and electricity intensity and their values depending on per capita according to data set are examined. Their graphs are created according to years and both real and normalized values are used. In addition, OECD, Non-OECD, world total and Turkey's energy intensity and electricity intensity are examined. It is found that while avregae of world total's energy intensity is getting better, developed countries' values converge lower energy inetensity values of average of world total and developing countries converge higher energy intensity values of average. While calculating energy and electricity convergence, histograms belongs to sigma convergence are applied. The purpose is to examine energy and electricity improvements depending on development frame and Turkey to compare obtained values according to terms given by data set 1971 and 2010. The first measuring that is used for energy intensity and electricity intensity is beta convergence. It tests catch up process whether it comes true or not for examining a country or a region. Some factors in a country, for example energy intensity can exhibit a fast moving. It is said that beta convergence can test such a value or decline of average growth rate at beginning of process. A negative and statistical significant value is specified for an indicator for beta convergence. Other convergence measure applied to calculations is called sigma convergence. It focuses the change of dispersion of the distribution concept. It is said that beta convergence is necessary, but not efficient for sigma convergence. Sigma convergence is important because it makes dispersion of the distribution be extended as soon as possible to be passed through the powerful countries by the old poor countires. In addition, sigma convergence measure catch up process that collects countries how effective is. It is put forward that sigma convergence has two measures to measure convergence in energy intensity and electricity intensity. One measure of sigma convergence is coefficient of variation (cv) that implies change between times (for example to normalize a value according to initial value). CV is achieved by standard deviation by dividing mean in energy or electricity intensity distribution for a country. If this measure declines in time, it means that convergence occurs. The other sigma convergence measure is Kernel density which depends on histograms that achieve if the distribution is changing in time. In the second measure of sigma convergence, the shape of the distribution is significant. The shape can be single mode, bimodal or multimodal. Multimodal and bimodal distribution is called as convergence clubs in convergence literature. In this study, sigma convergence's histogram measure is applied both energy intensity and electricity intensity of countries. When density of dispersion of distribution is measured, each countries' intensity is divided by current countries' group average for current year. Thus, it is achieved relative energy and electricity intensity. Then, each country is divided seven categories according to average: (

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