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Stručni rad

https://doi.org/10.7225/toms.v11.n01.w08

Regression Modelling Estimation of Marine Diesel Generator Fuel Consumption and Emissions

Onur Yüksel ; Dokuz Eylul University, Graduate School of Natural and Applied Sciences, İzmir, Turkey
Burak Köseoğlu ; Dokuz Eylul University, Maritime Faculty, İzmir, Turkey


Puni tekst: engleski pdf 5.250 Kb

str. 79-94

preuzimanja: 88

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Sažetak

This study aims to estimate the fuel consumption of marine diesel generators onboard. Objective technical specifications and operational data on the ship's power generating plants and port calls were collected from an oceangoing oil/chemical tanker and used to develop the mathematical model of the plant in the Python and MATLAB environment. The model consists of alternators, prime movers and load distributions of the ship’s power generating plant and provides information on fuel consumption in metric tons calculated based on hours of operation and specific fuel consumption data. Regression models have helped predict future fuel consumption for the plant and the optimal model for the dataset was identified by comparing four different algorithms. As the results have shown the Ordinary Least Squares Regression to be optimum, it was used to make one, five, and ten-year predictions. The predictions for one-year, five-year, and ten-year periods are 4,322,436, 10,684,860, and 18,615,472 t respectively. The selected model predicts fuel consumption with R2 of 0.999, MAE of 3.932, and RMSE of 2.935. Fuel consumption predictions facilitated plant emission calculation.

Ključne riječi

Marine diesel engines, Mathematical modelling, Linear regression, Support vector regression, Artificial neural networks, Time series analysis, Ship emissions

Hrčak ID:

283771

URI

https://hrcak.srce.hr/283771

Posjeta: 177 *