Title :
Coordinating Fuel Inventory and Electric Power Generation under Uncertainty
Author :
Takriti, S. ; Supatgiat, C. ; Wu, L. S-Y.
Author_Institution :
IBM Thomas J. Watson Research Center, Yorktown Heights, NY; University of Michigan, Ann Arbor, MI
fDate :
5/1/2001 12:00:00 AM
Abstract :
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-andbound solves the problem to optimality. Larger models are solved using Benders 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 four min to within 1.16% of the optimal value.
Keywords :
Economic forecasting; Fuels; Lagrangian functions; Natural gas; Power generation; Power industry; Power system modeling; Predictive models; Stochastic processes; Uncertainty; Benders decomposition; Lagrangian relaxation; branch-andbound; spark spread; stochastic programming; unit commitment;
Journal_Title :
Power Engineering Review, IEEE
DOI :
10.1109/MPER.2001.4311385