TY - JOUR
TI - A generalized disjunctive programming model for the optimal design of reverse electrodialysis process for salinity gradient-based power generation
AU - Tristán, C
AU - Fallanza, M
AU - Ibanez, R
AU - Ortiz, I
AU - Grossmann, I
T2 - Computers and Chemical Engineering
AB - Reverse electrodialysis (RED) is an emerging electro-membrane technology that generates electricity out of salinity differences between two solutions, a renewable source known as salinity gradient energy. Realizing full-scale RED would require more techno-economic and environmental assessments that consider full process design and operational decision space from the RED stack to the entire system. This work presents an optimization model formulated as a Generalized Disjunctive Programming (GDP) problem that incorporates a finite difference RED stack model from our research group to define the cost-optimal process design. The solution to the GDP problem provides the plant topology and the RED units’ working conditions that maximize the net present value of the RED process for given RED stack parameters and site-specific conditions. Our results show that, compared with simulation-based approaches, mathematical programming techniques are efficient and systematic to assist early-stage research and to extract optimal design and operation guidelines for large-scale RED implementation.
DA - 2023/02//
PY - 2023
PB - Elsevier
VL - 174
SP - 53
UR - https://www.sciencedirect.com/science/article/pii/S0098135423000650
DO - 10.1016/j.compchemeng.2023.108196
LA - English
KW - Salinity Gradient
KW - Reverse Electrodialysis
KW - Modeling
KW - Structural
KW - Cost Assessment
KW - Levelized Cost of Energy
ER -