بهره برداري بهينه از مخزن سد با ديدگاه تلفيقي آب سطحي و زيرزميني با استفاده از تكنيك هاي فازي

چكيده انگليسي :

Optimal Operation of Reservoir Using Management of Surface Water and Groundwater with Fuzzy Techniques Iman Chakraei Iman chakraei 1985@yahoo com February 28 2011 Department of Civil Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Dr Hamidreza Safavi Hasafavi@cc iut ac ir Abstract Operation of reservoirs involves complex decision making processes about release value that has been specified considering reservoir storage volume demands and prediction of inflow There are different models used for optimization and simulation Most of these techniques have been used for planning targets of stochastic systems however still having difference between theoretical models and practical s Optimization methods have been proved of much importance when used with simulation modeling and the two approaches when combined give the best results The managers and reservoir operators are often uncomfortable with the complicated optimization techniques used in the models which are made much more complex by inclusion of stochastic of hydrologic variables The fuzzy logic approach may provide a promising alternative for methods used for reservoir operation modeling Frequently the water releases from reservoir do not exactly follow the regular operating rule curves because of the uncertainty due to a variable hydrological condition consideration of specific social and economic factors and a regulating policy Operators can then play a major role for guiding the decision on water releases in such situations To deal with these uncertainties a fuzzy set theory has been used The water releases are decided based on operating policies which are developed by merging expert knowledge and observed data through the fuzzy rulebased model The significant advantage of the fuzzy logic is that it is obvious and easy to understand due to its rule based structure which emulates the human thinking even though specific release rules are not applied New emerging soft computing techniques such as Artificial Neural Network ANN Fuzzy logic and Neuro Fuzzy ANFIS can be gainfully employed to handle such problems when conditions of the systems are uncertain A neuro fuzzy system has the potential to capture the benefits of both neural network and fuzzy logic in a single framework Neuro fuzzy systems eliminate the basic problem in fuzzy systems design obtaining a set of fuzzy if then rules by effectively using the learning capability of an ANN for automatic fuzzy if then rule generation and parameter optimization As a result these systems can utilize linguistic information from the human expert as well as measured data during modeling Main target of this study has been made of operation rules of Zayandeh Rood reservoir using management of surface water and groundwater with inference of fuzzy system Adaptive Neuro Based Fuzzy Inference Systems ANFIS and fuzzy regression According to water shortage compared with demand in Zayandeh Rood basin and also dealing with groundwater intensive decrease in recent years groundwater decrease during the simulation period is restricted Then value of removable water from groundwater is calculated and deducted from sum of demands for domestic supply irrigation and industry Therefore share of Zayandeh Rood dam in preparation of downstream demands is obtained In this study various simulated models with performance evaluation criteria are compared In addition disability of Zayandeh Rood dam in satisfaction of all this basin demands is understood Results show that ANFIS model has made from optimal data yielded more sustainability than other models Key Word Optimization Model Simulation Model Dynamic Programming Fuzzy Model Adaptive Neuro Fuzzy Inference System ANFIS Fuzzy Regression Criteria of System Performance

چكرايي، ايمان

بهره برداري بهينه از مخزن سد با ديدگاه تلفيقي آب سطحي و زيرزميني با استفاده از تكنيك هاي فازي

مدل شبيه سازي , برنامه ريزي پويا , سيستم استنتاج فازي بر پايه شبكه عصبي تطبيقي﴿انفيس﴾ , رگرسيون فازي , معيارهاي عملكرد سيستم