Sammendrag
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.
Keywords: Liquefied natural gas supply chain, Decision support system,
Strategic planning, Stochastic mixed-integer linear programming
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.
Keywords: Liquefied natural gas supply chain, Decision support system,
Strategic planning, Stochastic mixed-integer linear programming