Abstract

Successful application of fuzzy control to an optimum control problem relies on the ability to make appropriate inferences from fuzzy information. In the reservoir operation problem, the operational rule adopted for simulation of the performance of a reservoir under historical or generated inflows, demands, etc. usually relates to the concept of an optimum release for the ‘current’ period. The main source of uncertainty in this process arises from the prediction of the value of the inflow during the current period. The value of this inflow is generally known in terms of its distribution. Since the storage volume at the end of each period is highly dependent on this inflow, it also is influenced by this uncertainty. Most stochastic simulation techniques for reservoir operation, however, operate on the basis of strict compliance to, or interpolation of, the operating policies and use as input stochastically generated inflows to account for the inflow uncertainty. Little attention, if any, is given to accounting for uncertainty in the decision itself. Since the optimum release decision obtained from a 3-state variable (storage volume at the beginning of the current period, the inflow in the previous time period, and the reservoir release during the current period) stochastic dynamic program is based on evaluation of the expected value of the return to the system, such a release decision should only be considered as a ‘guide’ such that, in certain circumstances, deviation of the release decision from the operating rule might be necessary. In this paper, a rational approach for selecting a release decision different from that envisaged in the operation rule is derived from application of the principles of fuzzy inference. The approach is demonstrated by application to the Wadaslintang Reservoir in Prembun, Central Java, Indonesia.

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