Optimal multiobjective reservoir operation with fuzzy decision variables and resources: A compromise approach

• The reservoir operation model is developed by considering the fuzzy parameters of the model.
• The releases, storage, maximum demands and maximum storages capacity of the reservoir are treated fuzzy.
• The parameters are represented by triangular fuzzy-number distribution.
• The defuzzified solution is used to develop the fuzzy compromise model.
• The model is solved by maximizing the degree of satisfaction (λ) by simultaneously optimizing both the objectives.

Imprecision is often involved in reservoir-systems operation, as these systems are too complex to be defined in precise terms. Fuzzy programming has an essential role in fuzzy modeling, which can formulate uncertainty in the actual environment. In this study, a multipurpose, single-reservoir operation model is developed by assuming triangular fuzzy-number distribution of the parameters. The applicability of the model is demonstrated through the case study of the Jayakwadi reservoir stage II, Maharashtra State, India. The reservoir-operation model considers two objectives: maximization of the releases for irrigation and maximization of the releases for hydropower generation. The model is solved for a vector of a triangular fuzzy-number by giving a priority to each objective. By individual optimization, the fuzzy optimal solution is obtained for each objective in the form of a triangular fuzzy-number distribution. This solution is defuzzified to obtain the crisp values, which are further used to develop a fuzzy-compromised model. The compromised model is solved for the maximization of the degree of satisfaction (λ) by simultaneously optimizing both of the objectives. The degree of satisfaction (λ) achieved is 0.67, and the corresponding values for irrigation releases and hydropower releases are equal to the 388.54 Mm3 and 195.19 Mm3, respectively.