The Users-Demand-Oriented Stochastic Scheduling Method on Seawater Desalination System

Abstract

In order to protect the water-supply scheme from the predictive error of water consumption, an user-demand oriented stochastic water-supply scheduling method on the seawater desalination system is proposed. Firstly, Classification and Regression Tree is used to estimate the prediction interval of the users’ future demands. Dependent-Chance Programming and Monte Carlo Simulation are used to figure out the probability of the event that the allocated water meets the demands of users. The equilibrium of water-supply is also taken into consideration. In this way, the stochastic model is transformed into the multi-objective optimization problem. Multiple-Population Quantum Genetic Algorithm is employed to acquire the optimal solution. The result of real-world case study validates the effectiveness of the proposed method.