Stochastic Mixed-Integer Programming for Integrated Portfolio Planning in the LNG Supply Chain

We present a new model to support strategic planning by actors in the liquefied natural gas market. The model takes an integrated portfolio perspective and addresses uncertainty in future prices. Decision variables include investments and disinvestments in infrastructure and vessels, chartering of v...

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Bibliographic Details
Published in:The Energy journal (Cambridge, Mass.) Mass.), 2014-01, Vol.35 (1), p.79-97
Main Authors: Werner, Adrian, Uggen, Kristin Tolstad, Fodstad, Marte, Lium, Arnt-Gunnar, Egging, Ruud
Format: Article
Language:English
Subjects:
Actors
Applied sciences
Benchmarking
Benchmarks
Business competition
Business logistics
Contract manufacturing
Decisions
Determinism
Economic data
Energy
Energy economics
Exact sciences and technology
Financial investments
Financial markets
Fossil fuels and derived products
Gas
General, economic and professional studies
Infrastructure (Economics)
Integer programming
Integers
Investment decisions
Investment portfolios
Investments
Liquefaction
Liquefied natural gas
Logistics
Market prices
Markets
Mathematical models
Methodology. Modelling
Natural gas
Natural gas industry
Net present value
Profits
Spot market
Stochastic models
Stochasticity
Supply chain management
Supply chains
Uncertainty
Vessels
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Summary:We present a new model to support strategic planning by actors in the liquefied natural gas market. The model takes an integrated portfolio perspective and addresses uncertainty in future prices. Decision variables include investments and disinvestments in infrastructure and vessels, chartering of vessels, the timing of contracts, and spot market trades. The model accounts for various contract types and vessels, and it addresses losses. The underlying mathematical model is a multistage stochastic mixed-integer linear problem. Industry-motivated numerical cases are discussed as benchmarks for the potential increases in profits that can be obtained by using the model for decision support. These examples illustrate how a portfolio perspective leads to decisions different than those obtained using the traditional net present value approach. We show how explicitly considering uncertainty affects investment and contracting decisions, leading to higher profits and better utilization of capacity. In addition, model run times are competitive with current business practices of manual planning.
ISSN:0195-6574
1944-9089
DOI:10.5547/01956574.35.1.5