This paper presents a two-phase artificial neural network approach for ending optimal scheduling of interconnected hydropower plants. In this approach the objective is to maximize hydropower generation and to satisfy the irrigation requirement as far as possible. A case study considering scheduling of Bhakra-Beas interconnected reservoir system is also presented in this paper. The proposed technique is compared with augmented penalty function methodology and demonstrates the potential of achieving better results.
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Naresh et al. (2000) studied this question.
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