Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Uygulamalı Matematik Enstitüsü, Finansal Matematik Anabilim Dalı, Türkiye
Tezin Onay Tarihi: 2016
Tezin Dili: İngilizce
Öğrenci: CANER FUAD YAZICI
Asıl Danışman (Eş Danışmanlı Tezler İçin): Sevtap Ayşe Kestel
Eş Danışman: Erkan Kalaycı
Özet:Natural gas is one of the main energy source in the world and plays an important role in energy demand. The liberalization process in the natural gas market has shifted the focus on the Local Distribution Companies (LDCs) which make the procurement and transportation decisions. The decisions such as the pipeline sales, Liquefied Natural Gas (LNG) sales, other sources of natural gas procurement, transportation and storage opportunities provide the LDCs an opportunity to trade the natural gas in a least-costs manner. It also makes the portfolio selection more complex for LDCs. The LDCs will consider other factors such as supply reliability, price uncertainty, demand uncertainty and other uncertain costs in a liberalized natural gas market. This study aims to develop an algorithm based on all contractual and technical real-world constraints for a gas import/wholesale company in the concept of flexibility. The methodology is applied to portfolio of contracts to produce the optimal amount of purchases and rates for the long term natural gas agreements, spot natural gas purchases, natural gas storage use levels and LNG purchases based on a real life case under various commitments such as Monthly Contract Quantity (MCQ) and Annual Contract Quantity (ACQ). Multivariate Adaptive Regression Splines (MARS) is applied to the natural gas supply to determine the pattern of the future demand by including factors like heating degree days (HDD), cooling degree days (CDD) and previous gas supply realizations. The output of the proposed methodology enables LDCs to develop criteria on producing the optimal future natural gas purchases depending on different oil scenarios proposed by World Energy Outlook (WEO) report, World Bank (WB) oil price forecasts and a stochastic oil price model (ARIMA) based on historical development of oil prices. A real life case study is applied to İstanbul which is a highly industrialized and populated metropolitan in Turkey. The data sets considering the natural gas demand were taken from İGDAŞ. The long term gas purchase price curves for different Take-or-Pay (ToP) rates are derived to guide the LDCs on their willingness to pay for long term natural gas contracts. LDCs assumed to act as a main supplier in this thesis.