Multi-objective optimization of RO desalination plants

A process optimization method has been developed for the design of reverse osmosis (RO) processes. RO process configurations are systematically generated using a flexible superstructure and evaluated by economical (investment and operating costs), technical (energy requirement, water recovery rate) and environmental performance indicators (Life Cycle Assessment). The simultaneous optimization of the RO process layout and operating conditions constitutes a mixed-integer nonlinear programming (MINLP) problem, which is solved using a multi-objective optimization (MOO) approach. The MOO identifies the best technological alternatives for the set of selected objectives. In a given context, it allows to define a set of optimal solutions representing the trade-off between conflicting objectives such as economical costs and environmental impacts. As a case study, the methodology is applied on a brackish water reverse osmosis (BWRO) desalination project, for which the optimal design is characterized depending on the economical conditions.

An advanced RO process design method has been developed, which allows to identify the best process RO process configurations for given project specifications. The RO process configurations are synthesized using a flexible superstructure and realistic spiral-wound membrane PV models for the representation of the reverse osmosis network. Their performances are evaluated by updated cost models and their environmental impacts are assessed with the electricity consumption and the total recovery rate being identified as representative values of RO process environmental performances. These performances indicators are used to optimize the RO process within a economical and environmental approach. A case study is presented for which the optimal layout and operating conditions are assessed. The optimal recovery rate is characterized as a function of the local context (e.g. feedwater salinity). The trade-off between environmental and economical objectives is identified by the definition of the permeate flux. For high permeate flux, low total costs are reached but electricity consumption and desalination environmental impacts are high. Low permeate flux allows to achieve lower electricity consumption but ought to be compensated by larger membrane area and higher costs. A second trade-off is identified between the two main impacts of desalination (electricity consumption and brine discharges). Indeed brine discharge can be reduced only with higher electricity consumption. The cost breakdown of these optimal configurations shows that the investment cost and the O&M cost remain approximately constant for the optimal configurations while cost variations result rather from the influence of operating conditions on power cost and membrane renewal cost. At last, the multi-objective optimization procedure is applied to other RO projects, in order to illustrate the flexibility of the design method. The solutions generated by the developed RO design method form a panel of various process alternatives adapted to the local context, from cost-optimal configurations to environmental friendly configurations, among which technology developers can choose according to their own weighting criteria and constraints.