Optimal Reservoir Operation Using Fuzzy Logic with Clustering Method

In this study a Fuzzy Based Model using a Non-Linear Programming to obtain optimal reservoir operation for irrigation of multiple crops is proposed. The reservoir level Fuzzy logic model can extract important features of the system from the inputoutput data set by Non-Linear Programming and represents features as general operating rules. The developed model can serve not only as efficient decision making tool in easy and understandable Fuzzy Inference Systems but also can provide operators with a limited number of the most meaningful operating rules usingClustering-Based approach. The model is set properly in a yearly base and monthlysteps. Results show that the changing trend of water releases in both models is the same with R2 = 0.97. Over the 12 months period, both trends had risen from October to May but since then they had fallen gradually. In general the amount of annual released water in Fuzzy model is almost less than NLP, especially in competitive months, May and June. The percentage of water deficit to the percentage of annual mean water deficit was respectively 0.57 and 0.81 in training and 0.93 and 1.145 in the test stage. The findings suggest that in the year with water deficit the amount of water release in competitive months to increase the Net Benefit should be more considered.

Keywords:

Reservoir Operation , Non-Linear Programming , Fuzzy Model , Clustering