Dizel motorlu kojenerasyon santralinin elektrik enerjisi üretiminin yapay sinir ağı (YSA) ile tahmini üzerine deneysel çalışma

Öz

Bu çalışmada iki adet V tipi 12 silindirli dizel motordan oluşan ve her biri 5.760 kW olmak üzere toplam 11.52 MW elektrik enerjisi üreten kojenerasyon enerji santralinin elektrik üretiminin tahmin edilmesi için yapay sinir ağı (YSA) geliştirilmiştir. 6 no'lu fuel oil ile çalışan kojenerasyon enerji santralinin elektrik enerjisi üretiminin (W) tahmini için geliştirilen YSA'da, zaman (t), çalışma saatleri (h), yakıt tüketimi (m) ve iç tüketim (Wp) değerleri giriş değişkenleri olarak kullanılmıştır. Farklı YSA'ların performansı değerlendirildikten sonra, bir gizli katman ve 10 nörondan oluşan YSA en ideal model olarak değerlendirilmiştir. Deneysel verilerle yapılan karşılaştırma sonucunda, bu modelin kojenerasyon enerji santralinin elektrik üretim değerlerini 0,99073 R değeri ve 4.734e-8 MSE ile tahmin edebileceği sonucuna varılmıştır.

Anahtar Kelimeler

• Kojenerasyon
• Dizel motor
• Enerji santrali
• Elektrik tüketimi
• Yapay Sinir Ağı

Experimental study for artificial neural network (ANN) based prediction of electric energy production of diesel engine based cogeneration power plant

Abstract

In this study artificial neural network (ANN) has been developed in order to estimate the electricity production of cogeneration power plant, which produces a total of 11.52 MW electric power, consisting of two V type and 12 cylinders each of which is 5.760 kW diesel engines running with heavy fuel oil no 6. In the ANN which was developed for the estimation of electric power generation of cogeneration, power plant(W), Time period (t), working hours (h), fuel consumption (m) and internal power consumption (Wp) values were used as input variables. After evaluating the performance of different ANNs, an ANN, consisting of one hidden layer and 10 neurons, was considered to be the most ideal one. As a result of the comparison with experimental data, it is concluded that this model estimates the electricity generation values of the cogeneration power plant with an R-value of 0,99073 and mean square error 4.734e-8.

Keywords

• cogeneration
• diesel engine
• Power plant
• Electricity consumption
• Artificial Neural Network

Kaynakça

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