The Acid/Base Flow Battery (AB-FB) is an innovative and sustainable way to store electric energy. It can theoretically guarantee an energy density of about 11 kWh/m3, which is higher than that provided by pumped hydropower, osmotic energy storage and compressed air. The AB-FB stores energy as pH and salinity gradients by employing a stack provided with (i) channels, hosting the solutions at difference pH and concentrations, separated by (ii) monopolar and bipolar ion exchange membranes. Two different membrane processes are involved: the Bipolar Membrane Electrodialysis (ED-BM) as charging step and its opposite, Bipolar Membrane Reverse Electrodialysis (RED-BM) as discharging step. The present work aims at predicting the performance of this AB-FB energy storage device via the development of a mathematical model based on a multi-scale approach. The channel represents the lowest scale of the model where Computational Fluid Dynamic Simulations are adopted to predict pressure drops and polarization phenomena. The middle-low-scale model concerns the triplet (which is the repeating unit of the stack) where all membrane fluxes (i.e. ohmic, diffusive, osmotic, etc.) are calculated. The middle-high-scale is devoted to predicting the pressure losses and the ionic losses (due to ionic short-circuit currents) in the manifolds. The highest scale includes all equations relevant to the connections of the stack with the tanks used to store the solutions. All model-scales are fully integrated, thus representing an original tool able to predict the flow battery performance parameters such as the power density produced and the overall battery round trip efficiency. A sensitivity analysis is performed by letting geometrical features (e.g. manifold size) and operating conditions (e.g. charge and discharge current density) to vary in a wide range of values. Main results show that the parasitic currents in the manifolds may represent the main limit to the present technology among all the detrimental phenomena. Suitable geometries and operating conditions can be adopted to reduce their effect thus leading to round-trip efficiencies higher than 65%.
Andrea Culcasi, Andrea Zaffora, Luigi Gurreri, Andrea Cipollina, Alessandro Tamburini, & Giorgio Micale (2019). On the modelling of an Acid/Base Flow battery: an innovative electrical energy storage device based on pH and salinity gradients. In 14th SDEWES conference Dubrovnik 2019 book of abstracts.
|Titolo:||On the modelling of an Acid/Base Flow battery: an innovative electrical energy storage device based on pH and salinity gradients|
|Data di pubblicazione:||2019|
|Progetto:||BAoBaB - Blue Acid/Base Battery: Storage and recovery of renewable electrical energy by reversible salt water dissociation|
|Citazione:||Andrea Culcasi, Andrea Zaffora, Luigi Gurreri, Andrea Cipollina, Alessandro Tamburini, & Giorgio Micale (2019). On the modelling of an Acid/Base Flow battery: an innovative electrical energy storage device based on pH and salinity gradients. In 14th SDEWES conference Dubrovnik 2019 book of abstracts.|
|Appare nelle tipologie:||2.08 Abstract in atti di convegno pubblicato in volume|