Algoritma Genetika Untuk Mengoptimasi Konsumsi Energi Pada Proses Kolom Distilasi Metanol-Air

Totok R. Biyanto
Journal article Jurnal Teknik Elektro Universitas Kristen Petra • Maret 2007 Indonesia


Distillation column has multivariable and nonlinear characteristics. High operation cost of distillation column required energy consumption optimization. The new alternative method to find out thelowestenergy consumtion of distillation column is optimization method using genetic algorithm. In this research, distillation model built up by neural network Multi Layer Perceptron (MLP) with Nonlinear Auto Regressive with eXternal input (NARX) structure, learning algorithm using Levenberg-Marquardt. Neural Network model has RMSE 3.9974x10-4 for condenser duty and RMSE 1.7435x10-4 for reboiler duty. Genetic algorithm optimization results are Qc 1.85E+07 and Qr 1.05E+07 which process variables are top pressure 106.846 Kpa, level condenser 30.289%, temperature feed 83.48 oC, fraction feed 0.5258, flow feed 493.518Kgmol/hour. In other word, there are decreasing steam and cooling water cost up to 46.2 %.


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Jurnal Teknik Elektro Universitas Kristen Petra

Jurnal Teknik Elektro Universitas Kristen Petra is published biannually, in May and September, by... tampilkan semua