Sürdürülebilir Kalkınma Amaçları

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• MakaleYalnız künye2013Scopus SJRQ1/r/gumushane/13193
  Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data

  Akpinar, Adem; Kömürcü, Murat I.hsan

  In this study, the existence and variability of wave energy resource potential of the Black Sea based on 15-year hindcast data is described in detail. The hindcasts of wave parameters were carried out by using the third generation wave prediction model (Simulated WAves Nearshore - SWAN), which is one of the most popular numerical wave models and has been widely used for estimating ocean waves. The model was forced with the ECMWF ERA Interim wind fields and applied with a spatial resolution of about 0.0167°. ×. 0.0167° and a model time step of 6. h to resolve efficiently offshore and nearshore wave conditions. The results were presented in the form of charts of the spatial distribution of significant wave height and wave power, on a monthly, seasonal and annual basis. Annual energy was calculated in the study region with the hindcast data set covering 15. years (1995-2009). The areas with the highest wave energy resource were determined and the south west coasts of the Black Sea are suggested as the best site for the installation of a wave farm. It was determined the western parts of the Black Sea (especially the south-west) are exposed to energetic waves more than the eastern parts.

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  AtıfScopus167·WoS155·OpenAlex180

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• MakaleYalnız künye2011Scopus SJRQ1/r/gumushane/15586
  Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables

  Kankal, Murat; Akpinar, Adem; Kömürcü, Murat Ihsan; Özşahin, Talat Şükrü

  This study deals with the modeling of the energy consumption in Turkey in order to forecast future projections based on socio-economic and demographic variables (gross domestic product-GDP, population, import and export amounts, and employment) using artificial neural network (ANN) and regression analyses. For this purpose, four diverse models including different indicators were used in the analyses. As the result of the analyses, this research proposes Model 2 as a suitable ANN model (having four independent variables being GDP, population, the amount of import and export) to efficiently estimate the energy consumption for Turkey. The proposed model predicted the energy consumption better than the regression models and the other three ANN models. Thus, the future energy consumption of Turkey is calculated by means of this model under different scenarios. The predicted forecast results by ANN were compared with the official forecasts. Finally, it was concluded that all the scenarios that were analyzed gave lower estimates of the energy consumption than the MENR projections and these scenarios also showed that the future energy consumption of Turkey would vary between 117.0 and 175.4. Mtoe in 2014.

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  AtıfScopus233·WoS199·OpenAlex282

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