Optimization of seawater desalination operations based on online prediction of water load

Abstract

The influence of uncertain changes in factors such as large fluctuations in water load and operating environment makes it difficult to achieve the expected cost reduction target for the optimization of fixed water dispatching plan and conventional forecast water consumption method, so an operation optimization method of desalination system based on moving average forecasting method and online updating of water production capacity of actual water load is proposed. First, the mathematical mechanism model of the reverse osmosis desalination system is established, the variation characteristics of the 24-hour cycle are simulated according to the operating parameters, and the optimization proposition aiming at the lowest cost within 24 hours is obtained. Then, through the analysis of the historical water consumption and production data from seawater desalination system, predicted water production schedule for the day ahead, and the later water production plan is continuously updated based on the obtained real-time water consumption data and the moving average prediction method data. The optimization problem containing differential-algebraic equations is discretized into a non-linear programming problem through finite element configuration. Combined with the online update prediction of water consumption, the system’s reverse osmosis desalination process optimization operation strategy is given. Finally, a case study on the optimal operation of the reverse osmosis seawater desalination system is carried out to verify the validity of the method proposed in this paper. The data results show that the proposed operation optimization method based on the moving average prediction and online update of the actual water load can achieve obvious cost reduction effect.