Using Z-Numbers in Determine Optimal Operation Parameters of Dam Reservoirs

Accurate estimation of water resources potential and their optimal use is a crucial issue in the water industry. Therefore, optimal reservoir operation is considered one of the most important management factors during dam operation periods. In real reservoir operations, decisions on water release are made, considering reservoir volume, demand quantities, and inflow forecasts. Given the uncertainty in dam reservoir operation data, one approach to addressing this uncertainty is through the use of fuzzy logic sets, as traditional fuzzy theories alone cannot fully account for the existing uncertainty in calculations. In this case, Z-numbers, as a new generation of fuzzy logic, have great potential in describing the uncertainty of human knowledge, as they consider both limitation and reliability.This research aims to determine optimal dam operation parameters for multi-step ahead considering data uncertainty and information reliability in optimization through Z-numbers, as a case study on the Alavian Dam. Efforts have been made to compare Z-number results with classical fuzzy logic, and genetic algorithm results. To evaluate these methods, performance indicators such as reliability, vulnerability, and stability were used, and the results showed that 77% of the genetic algorithm, 85% of classic fuzzy logic, and 92% of Z numbers of the needs related to the sustainable agricultural demand of Alavian Dam were met. The rule curve of optimal operating parameters obtained from Z-number modeling based on inflow forecasting through the method of Lower and Upper Bound Estimates (LUBE) showed that the observed release volume for Alavian Dam during the current flow year remained within the predicted range.