Temporal variation of power production via reverse electrodialysis using coastal North Carolina waters and its correlation to temperature and conductivity

Abstract

Global estimates of electricity generation from coastal salinity gradient energy resources rely on the underlying assumption that these gradients are spatially and temporally stable. Refining these estimates requires a better understanding of coastal variations in water properties and their impact on power production. This study investigated power output in reverse electrodialysis (RED) cells by coupling seawater samples collected from three different sites along coastal North Carolina at five different sampling dates between 2016 and 2017 with wastewater effluent from a wastewater treatment facility as the dilute solution. We found that power density did not vary substantially across the sampling dates except for one notable drop in power for a sample collected during an approaching hurricane. For all sites, power output peaked during the summer season. Using our experimental results, we developed a semi-empirical predictive model of RED power output as a function of temperature and conductivity. The model was able to predict power density within approximately 20% of the experimental power densities for the seawater samples used in this study and others in the literature. Combining our modeling approach with temporal conductivity and temperature data may help identify promising sites for coastal salinity gradient energy installations.

Ryan Kingsbury, Ph.D., P.E.

Assistant Professor

Ryan is an engineer and scientist working to accelerate development of advanced materials for water purification and clean energy production.