Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Conference Object
    Heat Load Factor for Geothermal District Heating System Design
    (National Technical University of Athens, 2006) Yıldırım, Nurdan; Gökçen, Gülden
    Design of heating systems using conventional fuels is based on peak load which is calculated according to the coldest outdoor design temperature. But in geothermal district heating system design it is common practice to use a heat load factor between 0.6-0.7 since the resource is continues, cheap and system can be run for 24 hours a day. Heat load factor can be defined as a ratio of actual heat load to design heat load of the system. In this study, a geothermal district heating system is designed for Izmir Institute of Technology Campus, Izmir, Turkey and simulated for a heat load factor range of 0.5-1. For the Campus case, the heat load factor is determined as 0.53-0.0.67 based on indoor air temperature and operational cost.
  • Conference Object
    Cash Flow Forecasting by Using Time Series Methods in Geothermal District Heating Systems: Balcova - Narlidere Case
    (National Technical University of Athens, 2006) Erdoğmuş, Abdullah Berkan; Özerdem, Barış
    Cash flow forecasting is one of the difficult and important tasks in an economic evaluation of a geothermal investment. Geothermal district heating systems are characterized by a high capital cost. In addition, relatively low operation and maintenance costs occur throughout their life. The aim of this research is to estimate the potential cash flows for Balcova - Narlidere Geothermal District Heating System by using historical data accumulated over a period of time and several forecasting methods: moving average, exponential smoothing, adjusted exponential smoothing and curve fitting functions. Mean absolute percentage deviation (MAPD) which is the most common approach to select the appropriate method to a particular time series is used in the selection of the most suitable model. Alternative methods are compared with each other regarding to their MAPD values. It is found that the models represented by exponential curve fitting functions have smaller MAPD values and give better results in cash flow forecasting of investment investigated.