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We discuss the problem of hedging between the natural gas
and electric power markets. Based on multiple forecasts for
natural gas prices, natural gas demand, and electricity
prices, a stochastic optimization model advises a decision
maker on when to buy or sell natural gas and when to
transform gas into electricity. For relatively small
models, branch-and-bound solves the problem to optimality.
Larger models are solved using Bender's decomposition and
Lagrangian relaxation. We apply our approach to the system
of an electric utility and succeed in solving problems
with 50,000 binary variables in less than 4 minutes to within
1.16% of the optimal value.
By: Samer Takriti, Chonawee Supatgiat, and Lilian S.-Y. Wu
Published in: IEEE Transactions on Power Systems, volume 17, (no 1), pages 13-18 in 2002
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