Multireservoir system optimization using fuzzy mathematical programming

For a multireservoir system, where the number of reservoirs is large, the conventional modelling by classical stochastic dynamic programming (SDP) presents difficulty, due to the curse of dimensionality inherent in the model solution. It takes a long time to obtain a steady state policy and also it requires large amount of computer storage space, which form drawbacks in application. An attempt is made to explore the concept of fuzzy sets to provide a viable alternative in this context. The application of fuzzy set theory to water resources systems is illustrated through the formulation of a fuzzy mathematical programming model to a multireservoir system with a number of upstream parallel reservoirs, and one downstream reservoir. The study is aimed to minimize the sum of deviations of the irrigation withdrawals from their target demands, on a monthly basis, over a year. Uncertainty in reservoir inflows is considered by treating them as fuzzy sets. The model considers deterministic irrigation demands. The model is applied to a three reservoir system in the Upper Cauvery River basin, South India. The model clearly demonstrates that, use of fuzzy linear programming in multireservoir system optimization presents a potential alternative to get the steady state solution with a lot less effort than classical stochastic dynamic programming.