Petroleum Sector Models

Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 222)


This chapter introduces the first building block of a comprehensive energy system optimization model with a discussion of the petroleum sector, formulated as a linear program. In Chapter 9 we build upon this model by integrating the refinery and electric sector LPs into a simple energy model appropriate to the energy planning problems of a developing country.


Cetane Number Octane Number Research Octane Number Motor Octane Number Reid Vapor Pressure 
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  1. 1.
    This discussion is taken, in some parts verbatim, from the 1978 EMTP presentation by F. Sebulsky and from J. D’Acierno and A. Hermelee “Physical Aspects of the U.S. Oil and Gas Systems” BNL 51076, Brookhaven Nationa Laboratory, November 1979.Google Scholar
  2. 2.
    For an excellent, but more detailed presentation of the technical aspects of refining, designed for the nonpetroleum engineer, see W. L. Leffler, “Petroleum Refining for the Non-Technical Person,” Petroleum Publishing Company, Tulsa, OK, 1979. An excellent but more technical book isGoogle Scholar
  3. 2a.
    J. Gary and G. Handwerk “Petroleum Refining: Technology and Economics,” Dekker, New York, 1975.Google Scholar
  4. 4.
    For further reading on LP models of refineries, see Murtagh (1981) or Ezzati (1978).Google Scholar
  5. 5.
    Such as the IMB-MPSX package for IBM Mainframe computers, or the APEX hydro package for CDC machines.Google Scholar
  6. 6.
    Murtagh (1981) is an excellent work in this respect, as it presents the special computational problems of large scale LP’s in the context of a refinery model example. The major problems of large scale LP’s concern computer storage limitations and the control of round-off error.Google Scholar
  7. 7.
    Many main-frame codes allow the entries of two row/column intersections per record (or card).Google Scholar
  8. 8.
    These solutions were obtained with LINPROG, an LP package for the IBM Personal Computer available from International Energy and Development Associates, 4726 Deer Run Court, Alexandria, VA 22306, U.S.A.Google Scholar
  9. 9.
    This is a rather simplified explanation; strictly speaking, the shadow price reflects the rate of change of the objective function at the optimum — changing the value of the rhs by 1 may or may not result in the expected change in the objective function.Google Scholar
  10. 10.
    Note that we have several variables in the basis at zero activity.Google Scholar
  11. 11.
    This discussion is based on Murtagh (1981).Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  1. 1.Institute for Energy ResearchState University of New York at Stony BrookStony BrookUSA

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