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Multi-objective optimization of hydropower reservoir operation Case study, Karoon 5
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Maryam Parhizkari   , Hamed Mazandarani zadeh |
| IKIU , mazandaranizadeh@gmail.com |
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Abstract: (815 Views) |
| Near the most of real-world decision-making issues, especially in the water resource management area, are multi-objective issues that are taken based on different and conflicting goals. Due to the wide range of application of these issues, different models have been proposed to solve them, NSGA-II and MOPSO are the most important of these multi-objective optimization models. The purpose of this study is to compare the performance of NSGA-II and MOPSO algorithms in solving multi-objective optimal operation of a hydropower reservoir. Due to the fact that the hydropower reservoirs are involved in providing the peak load of the network electricity, a neural network to predict daily energy prices in peak hours was developed initially, then the results were used to optimize the multi-objective operation of Karun 5 Dam reservoir, includes two goals of maximizing annual income and maximizing minimum daily energy production. Although the run time of the NSGA-II method is about twice as high as the MOPSO, the precision of its results is 20% better for both purposes than MOPSO. |
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| Keywords: Peak consumption, Peak Load, Neural Network, Electricity Network, PAB |
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Full-Text [PDF 316 kb]
(428 Downloads)
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Type of Study: Research |
Subject:
هیدرولوژی و برنامه ریزی منابع آب
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