Development And Application Of A Fuzzy Robust Optimization Programming Model For Management Of Seawater Desalination Systems Under Uncertainty

Due to the rapid population growth,climate change,the rapid development of urbanization and industrialization,and the serious pollution of existing freshwater resources,various regions of the world have different degrees of water scarcity problems.Seawater desalination is one of the effective ways to solve the water shortage But in the reality all the aspects of seawater desalination system management are subject to uncertainty.However,the existing optimization methods developed for seawater desalination system management can solve fewer kinds of uncertainties,the model application is limited and the model optimization cannot be guaranteed Therefore,in order to make up for the shortage of the optimization method for the management of seawater desalination system,it's necessary to develop a novel optimization approach to provide effective decision support for decision makersFirstly,this paper establishes a fuzzy robust optimization programming model.named FROP.for the management of seawater desalination system.Considering the aspects of the desalination technology selection and the capacity expansion of seawater desalination plants,the allocation of the desalted water and the control of the emission of the environmental pollutants.The optimization objective of the FROP model is to achieve economic goal of minimizing total system cost,and the developed model has set the constraints about the capacity of seawater extraction pump station,the emission of air pollutants,the production capacity of each desalination technology in each of seawater desalination.the desalted water demands and technical constraints.The fuzzy parameters in the model are quantified by trapezoidal possibility distribution,and the optimization robustness and feasibility robustness are considered in the objective function of the FROP model.The optimization robustness is used to control the solution optimality,and the feasibility robustness is used to control the model feasibility.Secondly,the FROP model is applied to a hypothetical seawater desalination system,and the optimal planning schemes are obtained,including the desalination technology selection and capacity expansion of each desalination plant and the allocation of desalted water.From the result analyses,at the beginning of the planning period,because of the economic objective of minimizing total system cost,all the desalination plants use DRO technology for the capacity expansion and desalted water generation due to this technology has relatively lower capital and operational costs.As the planning period progresses,due to the reduction of the maximum emissions of each air pollutant,the desalination plants begin to use the low-emission but costly desalination technology(MED and IRO)for the capacity expansion and the production of desalted water.Instead,the amount of desalted water produced by DRO technology is reduced.And then,making a comparison between the results generated by the FROP model and the deterministic model.It is found that the deterministic model only select the DRO technology to expand the production capacity and generate desalted water This is because that the economic objective of minimizing total system cost is the only optimization objectiveFinally,the influence of optimization robustness on the solution optimality,and the influence of feasibility robustness on the model feasibility are tested.In the model objective function,the solution optimality can be controlled by controlling the weight of optimization robustness in the model objective function.The larger the weight of the optimization robustness,the closer the final solution of the model is to the expected optimal solution.The model feasibility can be changed by changing the weight of feasibility robustness in the model objective function.The smaller the weight of the feasibility robustness,the smaller the feasibility of the model is.