Power consumption estimation using artificial neural networks: The case of Turkey
| dc.authorid | 0000-0002-8529-3775 | en_US |
| dc.contributor.author | Metin, Havva Hilal | |
| dc.contributor.author | Kaçtıoğlu, Sibkat | |
| dc.date.accessioned | 2019-08-09T09:35:37Z | |
| dc.date.available | 2019-08-09T09:35:37Z | |
| dc.date.issued | 2018 | en_US |
| dc.department | Fakülteler, Mühendislik ve Tasarım Fakültesi, Endüstri Mühendisliği Bölümü | en_US |
| dc.description.abstract | A significant proportion of the world energy consumption is by developing countries. As a developing country, Turkey is one of the leading countries in terms of the increase in energy demand. According to the data from the Ministry of Energy and Natural Resources, Turkey is the country with the greatest increase in demand after China in electricity and natural gas consumption since 2000. In 1970, the ratio of total energy production to consumption in Turkey was 76%. In year 2000, this ratio dropped down to 35%, in year 2010 to 26% and predicted to come down to 23% by year 2020. This situation indicates an increase in Turkey’s energy dependency every passing year and the need to implement solutions to reduce this dependency. Today, electric energy has become a very critical and indispensable part of the development of technology. Production and consumption of electrical energy, which facilitates human life and increases labour productivity, are increasing every year. Electricity is a versatile and easily controlled form of energy. Electricity is practically non-existent and non-polluting at the point of use. Electricity can be cleanly produced by completely renewable methods such as wind, water and sunlight at the production point. Electricity market has a unique feature compared to other commodities. This feature requires the consumption of electricity when it is produced. Forecasting the future consumption of electricity in Turkey is crucial in making strategic plans for the future and taking the necessary measures. In Turkey, the consumption of electricity in the estimation studies were generally observed that the use of long-term electricity consumption prediction method of neural networks. In some studies, the results obtained by artificial neural network method are compared with Box-Jenkins models and regression technique. As a result of comparison, artificial neural networks seem to be a good predictor of electricity consumption. In this study, electrical consumption is modelled by using artificial neural network method and the results are discussed. In the application, the four main factors that affect the electricity consumption in Turkey is considered as independent variables. These independent variables are; Population, Imports, Exports, Gross Domestic Product (GDP). How these independent variables affect the electricity consumption in the country was found as the result of the tests made and the results were evaluated. | en_US |
| dc.identifier.endpage | 91 | en_US |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.startpage | 81 | en_US |
| dc.identifier.uri | https://hdl.handle.net/11467/2864 | |
| dc.identifier.volume | 4 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Jital | en_US |
| dc.relation.ispartof | Journal of International Trade, Logistics and Law, | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Electric Energy | en_US |
| dc.subject | Prediction | en_US |
| dc.subject | Future | en_US |
| dc.subject | Artificial Neural Networks | en_US |
| dc.subject | Electricity Consumption Estimation | en_US |
| dc.title | Power consumption estimation using artificial neural networks: The case of Turkey | en_US |
| dc.type | Article | en_US |
