%0 Journal Article %A parhizkari, maryam %A mazandarani zadeh, hamed %T Multi-objective optimization of hydropower reservoir operation Case study, Karoon 5 %J Iranian Dam and Hydroelectric Powerplant %V 8 %N 30 %U http://journal.hydropower.org.ir/article-1-412-en.html %R %D 2021 %K Peak consumption, Peak Load, Neural Network, Electricity Network, PAB, %X 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. %> http://journal.hydropower.org.ir/article-1-412-en.pdf %P 24-32 %& 24 %! Multi-objective optimization of hydropower reservoir operation %9 Research %L A-10-397-3 %+ IKIU %G eng %@ 2322-5882 %[ 2021