TY - CONF
T1 - Optimisation analysis of Reverse Electrodialysis systems for power production from concentrated brines
AU - Cipollina, Andrea
AU - Micale, Giorgio Domenico Maria
AU - Tamburini, Alessandro
AU - Tedesco, Michele Alessandro
PY - 2016
Y1 - 2016
N2 - Reverse Electrodialysis (RED) is rapidly growing as technology to produce electric energy by mixing saline solutions with different salinity. Recent developments have shown promising results on real site installations, demonstrating the feasibility of the RED process on the pilot scale. Therefore, further modelling efforts are now needed to optimise the technology, in order to enhance the performance.In this work, an optimisation study for the RED process is presented, taking into account saline waters and concentrated brine as feed streams. The model, which is developed within GAMS environment, predicts the optimal set of process variables that maximise the process yield, as well as the gross and net power density. The influence of various site-dependent parameters are investigated, identifying the optimal operating conditions for different feed streams.The model shows that different optimal operating conditions can be identified, according to the specific conditions of the feeds and the target of the process. In particular, lower fluid velocities are preferable to maximize the net power density, while larger stack size leads to higher process yields. Finally, optimal stack designs are discussed, showing the effect of different technological strategies on the large-scale power production.
AB - Reverse Electrodialysis (RED) is rapidly growing as technology to produce electric energy by mixing saline solutions with different salinity. Recent developments have shown promising results on real site installations, demonstrating the feasibility of the RED process on the pilot scale. Therefore, further modelling efforts are now needed to optimise the technology, in order to enhance the performance.In this work, an optimisation study for the RED process is presented, taking into account saline waters and concentrated brine as feed streams. The model, which is developed within GAMS environment, predicts the optimal set of process variables that maximise the process yield, as well as the gross and net power density. The influence of various site-dependent parameters are investigated, identifying the optimal operating conditions for different feed streams.The model shows that different optimal operating conditions can be identified, according to the specific conditions of the feeds and the target of the process. In particular, lower fluid velocities are preferable to maximize the net power density, while larger stack size leads to higher process yields. Finally, optimal stack designs are discussed, showing the effect of different technological strategies on the large-scale power production.
UR - http://hdl.handle.net/10447/191691
M3 - Other
SP - 299
EP - 300
ER -