2003•Unpublished venueRequires access

Intelligent management and control of fuel gas network

A. De Carli, S. Falzini, Raffaele Liberatore, D. Tomei

Open publisher page 3 citations

Abstract

The design procedure of an advanced controller for the fuel gas network of a refinery is illustrated. Its purpose is to improve the performance of the heat generators using fuel gas and fuel oil as combustible and to reduce the operation that reduce the refinery efficiency. Soft computing approaches are widely used to attain the desired results. Fuzzy logic and genetic algorithms allow attaining the desired results. A simulation model of the fuel gas network functionality allows to design and to validate the advanced controller functionality. Dedicated simulation test focused the obtained advantages in the management of the refinery process.

About this research paper

What this paper is about

The design procedure of an advanced controller for the fuel gas network of a refinery is illustrated. Its purpose is to improve the performance of the heat generators using fuel gas and fuel oil as combustible and to reduce the operation that reduce the refinery efficiency. Soft computing approaches are widely used to attain the desired results. Fuzzy logic and genetic algorithms allow attaining the desired results. A simulation model of the fuel gas network functionality allows to design and to validate the advanced controller functionality. Dedicated simulation test focused the obtained advantages in the management of the refinery process.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The design procedure of an advanced controller for the fuel gas network of a refinery is illustrated. Its purpose is to improve the performance of the heat generators using fuel gas and fuel oil as combustible and to reduce the operation that reduce the refinery efficiency. Soft computing approaches are widely used to attain the desired results. Fuzzy logic and genetic algorithms allow attaining the desired results. A simulation model of the fuel gas network functionality allows to design and to validate the advanced controller functionality. Dedicated simulation test focused the obtained advantages in the management of the refinery process.

Key concepts: Refinery, Controller (irrigation), Process (computing), Computer science, Fuel oil, Process engineering, Control engineering, Automotive engineering

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