optimization of hydropower reservoir operation using artificial neural networks
Publish place: Symposium on Uncertainty Assessment in Dam Engineering
Publish Year: 1384
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
SUADE01_006
تاریخ نمایه سازی: 15 آبان 1390
Abstract:
After development of any optimization model a post-optimization simulation is needed for two purposes: 1) Checking and evaluating of system performance and 2) Computing performance criteria. The common rule is developing a simulation model in the form of a computer code. In this paper, using stochastic dynamic programming, the optimum operating rule of a hydropower system is derived. Then capability of artificial neural networks (ANNs) has assessed as a substitution of simulation model. The optimization model has divided to 50 classes of discrete storage volumes and 8 classes of inflows in each time period. Derived optimum rules then have applied for ANN model training. Then the optimum releases of a 43 year historical record has determined with simulation model and ANN model, as model testing. The results show that the optimum releases of reservoir inboth ANN and simulation models are very close together
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Authors
O. BOZORG HADDAD
Iran university of science and Technology, Tehran, Iran
S. ALIMOHAMMADI
Water Engineering Department, Shahid Abbaspoor University; Water Resources Expert, Moshanir Power Engineering Consultant
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