A Leader-Follower Game-Based Life Cycle Optimization Framework and Application

Jiyao Gao, Fengqi You

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

In this work, we address the life cycle optimization of a shale gas supply chain covering the well-to-wire life cycle of shale gas-generated electricity. A non-cooperative supply chain with multiple players is considered. Following the Stackelberg game, the power generation sector is identified as the leader in this game that takes action first and cares about both its own cost and the greenhouse gas emissions across the product life cycle. After the observation of power plants’ decisions, the follower as shale gas producer takes actions correspondingly to optimize its own profit. Both players need to make both design and operational decisions. The resulting problem is formulated as a multiobjective mixed-integer bilevel linear programming problem, which cannot be solved using any off-the-shelf solvers directly. Based on a case study of the Marcellus shale play, the levelized cost of electricity ranges from $75/MWh to $133/MWh, and the corresponding unit greenhouse gas (GHG) emissions range from 111 to 469 kg CO2-eq/MWh. The application of carbon capture and storage implies significant impacts on both economic and environmental performance. The non-cooperative supply chain has a 9% higher upstream GHG emissions compared with the cooperative one.

Original languageEnglish (US)
Title of host publication26 European Symposium on Computer Aided Process Engineering, 2016
PublisherElsevier B.V.
Pages541-546
Number of pages6
Volume38
ISBN (Print)9780444634283
DOIs
StatePublished - Jan 1 2016

Publication series

NameComputer Aided Chemical Engineering
Volume38
ISSN (Print)1570-7946

Keywords

  • game theory
  • life cycle optimization
  • MIBLP
  • shale gas

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

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