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Electric energy demands of Turkey in residential and industrial sectors

机译:土耳其在住宅和工业领域的电能需求

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The main objective of the present study is to apply the artificial neural network (ANN) methodology, linear regression (LR) and nonlinear regression (NLR) models to estimate the electricity consumptions of the residential and industrial sectors in Turkey. Installed capacity, gross electricity generation, population and total subscribership were selected as independent variables. Two different scenarios (powerful and poor) were proposed for prediction of the future electricity consumption. Obtained results of the LR, NLR and ANN models were also compared with each other as well as the projection of the Ministry of Energy and Natural Resources (MENR) and the results in literature. Results of the comparison showed that the performance values of the ANN method are better than the performance values of the LR and NLR models. According to the poor scenario and ANN model, Turkey's residential and industrial sector electricity consumptions will increase to value of 140.64TWh and 124.85 TWh by 2015, respectively.
机译:本研究的主要目的是应用人工神经网络(ANN)方法,线性回归(LR)和非线性回归(NLR)模型来估算土耳其住宅和工业部门的电力消耗。选择装机容量,总发电量,人口和总订户数量作为自变量。为了预测未来的用电量,提出了两种不同的情况(有力和有力)。还比较了LR,NLR和ANN模型获得的结果,以及能源和自然资源部(MENR)的预测以及文献中的结果。比较结果表明,ANN方法的性能值优于LR和NLR模型的性能值。根据糟糕的情景和人工神经网络模型,到2015年,土耳其的住宅和工业用电量将分别增加到140.64TWh和124.85TWh。

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