Modelling, investment planning and optimisation for the design of a polygeneration energy system

Pei Liu*, Dimitrios I. Gerogiorgis, Efstratios N. Pistikopoulos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract / Description of output

The forecasted shortage of fossil fuels and the ever-increasing effect of greenhouse gas (GHG) emissions on global warming and environmental stability are two international problems with major technical, economic and political implications in the 21st century. Therefore, it is urgent to restructure present energy production and utilization systems in order to ensure that fossil fuels are used with high efficiency and low to zero emissions. Polygeneration energy systems combine power generation and chemical fuel synthesis in a single plant (producing both electricity and fuels) and thus provide a promising alternative pathway towards achieving sustainable and flexible economic development. Mixed-integer programming (MIP) is useful in constructing long-term decision models that are suitable for investment planning and design of polygeneration infrastructure systems. This paper presents a model for the investment planning of a polygeneration energy system, and uses this model for a case study addressing a system for production of methanol and electricity.

Original languageEnglish
Title of host publication17th European Symposium on Computer-Aided Process Engineering (ESCAPE-17)
EditorsV Plesu, PS Agachi
Place of PublicationAMSTERDAM
PublisherElsevier B.V.
Number of pages8
ISBN (Print)978-0-444-53157-5
Publication statusPublished - 2007
Event17th European Symposium on Computer Aided Process Engineering (ESCAPE-17) - Bucharest, Romania
Duration: 27 May 200730 May 2007

Publication series

NameComputer-Aided Chemical Engineering
ISSN (Print)1570-7946


Conference17th European Symposium on Computer Aided Process Engineering (ESCAPE-17)

Keywords / Materials (for Non-textual outputs)

  • polygeneration
  • energy
  • mixed-integer programming
  • optimisation


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