Modeling uncertainty in reservoir loss functions using fuzzy sets

Imprecision involved in the definition of reservoir loss functions is addre ssed using fuzzy set theory concepts. A reservoir operation problem is solv ed using the concepts of fuzzy mathematical programming. Membership functio ns from fuzzy set theory are used to represent the decision maker's prefere nces in the definition of shape of loss curves. These functions are assumed to be known and are used to model the uncertainties. Linear and nonlinear optimization models are developed under fuzzy environment. A new approach i s presented that involves development of compromise reservoir operating pol icies based on the rules from the traditional optimization models and their fuzzy equivalents while considering the preferences of the decision maker. The imprecision associated with the definition of penalty and storage zone s and uncertainty in the penalty coefficients are the main issues addressed through this study. The models developed are applied to the Green Reservoi r, Kentucky. Simulations are performed to evaluate the operating rules gene rated by the models considering the uncertainties in the loss functions. Re sults indicate that the reservoir operating policies are sensitive to chang e in the shapes of loss functions.