Reverse Electrodialysis (RED) harvests electrical energy from a salinity gradient. The maximumobtainable net power density (NPD) depends on many physical and geometric variables. Somehave a monotonic (beneficial or detrimental) influence on NPD, and can be regarded as “scenario”variables chosen by criteria other than NPD maximization. Others, namely the thicknesses HCONC,HDIL and the velocities UCONC, UDIL in the concentrate and diluate channels, have contrastingeffects, so that the NPD maximum is obtained for some intermediate values of these parameters.A 1-D model of a RED stack was coupled here with an optimization algorithm to determine theconditions of maximum NPD in the space of the variables HCONC, HDIL,UCONC, UDIL for differentcombinations of the “scenario” variables. The model accounts for entrance effects, propertyvariation, concentration polarization, axial concentration changes, osmotic, electro-osmotic anddiffusive fluxes, and can deal with complex channel geometries using Ohmic resistances, frictionfactors and mass transfer coefficients computed by 3-D simulations.
|Title of host publication||13th SDEWES conference Palermo 2018 book of abstracts|
|Number of pages||1|
|Publication status||Published - 2018|