Modeling of Ionic Shortcut Currents in RED and ED with segmented electrodes - An open-source approach to stack modeling with Python and ngspice

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dc.contributor.authorTenblad, Pauline
dc.contributor.departmentChalmers tekniska högskola / Institutionen för arkitektur och samhällsbyggnadsteknik (ACE)sv
dc.contributor.examinerModin, Oskar
dc.date.accessioned2020-11-19T09:52:55Z
dc.date.available2020-11-19T09:52:55Z
dc.date.issued2020sv
dc.date.submitted2020
dc.description.abstractIn the battle against global warming, reducing greenhouse gases is of utmost importance. Salinity gradient energy is a clean renewable energy source where energy is generated by mixing waters of different salinity. To harvest this energy reverse electrodialysis (RED) can be used. High energy efficiency is fundamental for upscaling the process and make it commercializable. A factor limiting the efficiency is the occurrence of ionic shortcut currents (ISCC). They arise from voltage differences within the stack and lead to loop-back of the current, resulting in a lower current coming out of the stack and thus a lower power production. Previous work have investigated the impact electrode segmentation has on the power production and found that electrode segmentation can improve the power production in RED stacks. These studies have assumed ideal stack properties and failed to take the occurrence of ionic shortcut currents into account. The object of this project has therefore been to investigate the role of ionic shortcut currents on the performance of electrode segmentation and to investigate if the ISCC limit the benefit of electrode segmentation. A model was created that simulates the process as an electric circuit. It uses the RED model created by Simoes et al. (Desalination, vol. 492, p. 114604, 2020) to calculate the internal resistance, the electromotive force and resistances of the shortcut currents for each cellpair forming the stack. The model created in this project can be used to simulate both a reverse electrodialysis stack and an electrodialysis stack (where energy is applied to the system to drive the salinity gradient, i.e. to desalinate one stream and form a brine stream). It was found that a 2x2 segmented stack outperformed the unsegmented stack for stacks with the number of cellpairs composing the stack ranging from 10 to approximately 100 cellpairs. For larger stacks, the power output of the segmented stack dropped drastically while the power output of the unsegmented plateaued. The results suggest that the ionic shortcut currents inhibit the advantages of the segmentation when the stack becomes too big. However, there is still a need to further validate these results. Further investigations with different cell sizes, flow rates and segmentation configurations are advised. The results show that for an increased amount of cellpairs forming the stack, the impact of the ionic shortcut currents is increased. In future studies, investigating alternatives to reduce the ISCC, for example with special manifolds, is encouraged.sv
dc.identifier.coursecodeACEX30sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/302065
dc.language.isoengsv
dc.setspec.uppsokTechnology
dc.subjectSalinity gradient energysv
dc.subjectReverse electrodialysissv
dc.subjectRenewable energysv
dc.subjectEnergy efficiencysv
dc.subjectIonic shortcut currentssv
dc.subjectParasitic currentssv
dc.subjectStack designsv
dc.subjectCurrent leakagesv
dc.subjectModelingsv
dc.subjectOptimizationsv
dc.titleModeling of Ionic Shortcut Currents in RED and ED with segmented electrodes - An open-source approach to stack modeling with Python and ngspicesv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
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