Performance analysis of a reverse electrodialysis stack for electricity generation in KZN, SA

Abstract

The Earth is now 1.1 ℃ warmer than in the 19th century, with a 50% surge in atmospheric CO2 levels. Climate scientists stress the importance of limiting global warming to 1.5 ℃ by 2100, emphasizing the need for immediate action. However, without intervention, projections suggest a potential temperature rise exceeding 2 ℃ or even reaching 2.4 ℃ by the end of this century. Failure to address this issue could result in catastrophic consequences, including severe heatwaves, widespread displacement due to rising sea levels, and irreversible damage to plant and animal species. The urgency to curb greenhouse gas emissions and mitigate the impacts of climate change is paramount to safeguarding the future of the planet. In 2015, leaders of different countries made a crucial global initiative in Paris, France—the Paris Agreement. This agreement addresses urgent climate challenges, recognizing that failure to tackle climate change could lead to catastrophic consequences, from severe heatwaves to the irreversible loss of biodiversity. By committing to curb greenhouse gas emissions, the Paris Agreement provides a vital framework for safeguarding the planet's future and fostering international collaboration in the face of climate adversity. South Africa faces a critical energy challenge marked by frequent load shedding and heavy reliance on coal-based electricity generation. The energy sector plays a pivotal role in the nation's socio-economic development, and the persistent power shortages have significant repercussions on industrial output, livelihoods, and environmental sustainability. This precarious situation necessitates a shift towards sustainable and renewable energy sources. In February 2020, South Africa released its Low Emission Development Strategy, with the goal of achieving a net-zero carbon economy by 2050. This dynamic strategy provides flexibility for South Africa to adapt its approach, considering emerging innovations and alternative energy options. One promising avenue is the utilization of Reverse Electrodialysis (RED) technology, which harnesses the salinity gradient between concentrated solutions usually seawater and less concentrated solution usually river water to generate electricity. Despite its potential, the integration of RED technology into South Africa's energy landscape remains underexplored and underutilized. This research aims to investigate the parameters that affects power generation in a RED stack using local waters. The impact of electrode rinse solution on the stack remains a scarcely explored area. Despite the significant advancements in RED technology, there is a notable gap in understanding the effect of electrode rinse solutions on RED stack performance. The study was divided into three parts. The first part of the study involved comparing the effects of different electrode rinse solutions (ERS) on open-circuit voltage (OCV), power density, and internal resistance. The solutions tested included Potassium Chloride (KCl), Sodium Chloride (NaCl), Sodium Sulphate (Na2SO4), and a mixture of Potassium Ferricyanide anhydride, Potassium Ferrocyanide trihydrate, and Sodium Chloride [K3Fe(CN)6, K4Fe(CN)6, and NaCl]. The comparison was based on Open Circuit Voltage (OCV), Voltage Under Load (VUL), internal resistance, and power density. Variables investigated included the flow rate of the rinse solution, concentration, and composition. The flow rate of the ERS was varied from 9.15 to 18.3 L/h, and the concentration was varied from 5 to 30 g/L. But for the mixture, four of the most commonly used molar concentrations in literature were chosen. The experiments were conducted at room temperature (25 ℃ ± 0.5). The feed comprised of synthesized sodium chloride solutions flowing at a constant rate of 900 mL/min, with concentrations of 0.4 g/L for the less concentrated solution and 38 g/L for the more concentrated solution. The results indicated that the ERS significantly influences the power generation of the stack. The mixture demonstrated the best performance in terms of OCV, VUL, internal resistance, and power density. This superior performance can be attributed to the presence of redox species in the mixture. The highest recorded values for OCV, VUL, and power density were 4.354 V, 0.966 V, and 8.964 W/m2 , respectively, and these were exclusively measured when using the mixture as an ERS. When comparing the highest power density measurement for the mixture to the highest power density measurement for KCl solution, a notable difference of 73% was observed. Additionally, the lowest internal resistance recorded was 14.26 Ω, and it occurred with the mixture as the ERS. The second part of the study involved using seawater and various river water samples as feed solutions, with manipulated variables including the temperature and flow rate of the feed. The temperature ranged from 25 to 40 ℃, and the flow rate varied between 900 and 1550 mL/min. The ERS was circulated at a constant flow rate of 153 mL/min. Results indicated that temperature had a more pronounced effect on power generation compared to flow rate. Notably, the highest increase in power density was 60.0% from a temperature of 25 to 40 ℃. On the other hand, the highest increase in power density was 31.3% from a flow rate of 900 to 1550 mL/min. Internal resistance was significantly influenced by temperature, with the lowest values consistently observed at the highest temperatures and flow rates. In the final part of the study, a software tool, Design Expert, was employed to identify the optimum point for the system. uMkomaas river water sample was utilized for this analysis. Data of the runs was feed to the Design Expert software under historical data. Low coded factors, which is -1, were 900 and 25 for flow rate and temperature, respectively. High coded factors, which is 1, were 1550 and 40 for flow rate and temperature, respectively. The responses of the system were OCV and VUL. ANOVA was used to analyze the system’s historical data and optimize the process. The order of optimization was Quadratic. The adjusted R2 for OCV and VUL were 0.8048 and 0.6484, respectively. The surface response was analyzed. The optimum conditions achieved a desirability of 92.7%. Four runs were conducted as confirmation.