Optimization of the power generation scheduling in oil-rig platforms using genetic algorithm

Parikshit Yadav, Rajesh Kumar, S. K. Panda, C. S. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

The paper focuses on the optimal scheduling of the diesel generators in the oil rig platform for the fuel optimization problem. The Specific Fuel Consumption (SFC) of the Diesel Generator is not properly modeled in the literature. An accurate model of SFC using cubic spline interpolation method is also presented. Optimization of fuel consumption at various loading conditions has been analyzed with efficient use of load scheduling of the diesel generators. The SFC model consists of discrete and non linear equations and hence conventional method fail to provide optimal solution. The Genetic Algorithm (GA) is proposed for the optimum load scheduling of diesel generators of both equal and unequal ratings. A comparison of all the methods is also presented to obtain the probable optimal solution of the problem. It is concluded that proposed SFC model is more accurate and GA gives better results than conventional methods. The proposed schemes can be used in marine power plant design and are equally applicable for any other technology.

Original languageEnglish
Title of host publicationISIE 2010 - 2010 IEEE International Symposium on Industrial Electronics
Pages2292-2297
Number of pages6
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 IEEE International Symposium on Industrial Electronics, ISIE 2010 - Bari, Italy
Duration: 4 Jul 20107 Jul 2010

Publication series

NameIEEE International Symposium on Industrial Electronics

Conference

Conference2010 IEEE International Symposium on Industrial Electronics, ISIE 2010
Country/TerritoryItaly
CityBari
Period4/07/107/07/10

Keywords

  • Cubic spline interpolation
  • GA
  • Optimization
  • Specific fuel consumption

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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