A hybrid method for hydroelectric generation scheduling using an artificial neural network

A hybrid method for hydroelectric generation scheduling using an artificial neural network

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Article ID: iaor2002264
Country: United States
Volume: 31
Issue: 2
Start Page Number: 263
End Page Number: 271
Publication Date: Feb 2000
Journal: International Journal of Systems Science
Authors: ,
Keywords: scheduling, neural networks
Abstract:

This paper presents a decomposition method for finding an optimal operating policy of interconnected hydroelectric power plants using an artificial neural network. The coupling constraints on reservoir storage at the end of the planning horizon are relaxed using coordinating multipliers that result in interval wise decomposition of the overall problem. Resulting subproblems are solved sequentially, which reduces the complexity of the problem. Each subproblem is solved using a two-phase neural network approach. An efficient heuristic algorithm is developed to find the feasible solution. A ease study considering scheduling of the Bhakra-Beas reservoir system is also presented in this paper. The new method demonstrates the potential of achieving an improved performance.

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