Quantifying Chlorine Gas Evolution from Mixed-Acid Vanadium Redox Flow Batteries.
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Graphitized carbon nanofibers (CNFs) are the allotropic forms of carbon that offer exceptional electrical conductivity, high aspect ratio, large surface-to-volume ratio, flexibility, mechanical robustness, and structural stability. These properties render CNFs as useful materials in energy applications, including water electrocatalysis and electrochemical energy storage devices (EESDs). Graphitized CNFs manifest huge versatility in EESDs and have been employed as electrode materials, as supports for other electrode materials, and conductive additives. This perspective summarizes the production methods, structural aspects, and energy applications of graphitized CNFs. Different design strategies have been employed to produce CNFs with diverse and distinct morphologies and structures. Their fabrication methods, along with precursors and dopants or cocatalysts, impact the overall structural, functional, and topographical properties. Recent developments on the state-of-the-art interests of graphitic CNFs in lithium-ion batteries (LIBs), lithium–sulfur (Li–S) batteries, vanadium redox flow batteries (VRFBs), supercapacitors, and water splitting have explored the many possibilities in energy sectors. Finally, the assembly and functioning of CNFs in water splitting and EESDs as well as primary challenges are discussed in this perspective.
In support of the U.S. Department of Energy’s Energy Storage Grand Challenge, Pacific Northwest National Laboratory is applying its rich history of battery research and development to provide the U.S. Department of Energy (DOE) and industry with a guide to current energy storage costs and performance metrics for various technologies. Cost and performance metrics for individual technologies track the following to provide an overall cost of ownership for each technology: cost to procure, install, and connect an energy storage system; associated operational and maintenance costs; and end-of-life costs. These metrics are intended to support DOE and industry stakeholders in making sound decisions about future R&D directions and priorities that move the United States closer to its goal of energy independence. The technologies currently being evaluated are lithium-ion [lithium iron phosphate (LFP) and nickel manganese cobalt (NMC)] batteries, vanadium redox flow batteries, lead-acid batteries, zinc-based batteries, hydrogen energy storage, pumped storage hydropower, gravitational energy storage, compressed air energy storage, and thermal energy storage.
All-vanadium sulfate redox flow battery systems have a catholyte and an anolyte comprising an aqueous supporting solution including chloride ions and phosphate ions. The aqueous supporting solution stabilizes and increases the solubility of vanadium species in the electrolyte, allowing an increased vanadium concentration over a desired operating temperature range. According to one example, the chloride ions are provided by MgCl2, and the phosphate ions are provided by (NH4)2HPO4.
All-vanadium sulfate redox flow battery systems have a catholyte and an anolyte comprising an aqueous supporting solution including chloride ions and phosphate ions. The aqueous supporting solution stabilizes and increases the solubility of vanadium species in the electrolyte, allowing an increased vanadium concentration over a desired operating temperature range. According to one example, the chloride ions are provided by MgCl 2 , and the phosphate ions are provided by (NH 4 ) 2 HPO 4 .
Vanadium redox couples (V(II)/V(III) on a negative electrode or V(IV)/V(V) on a positive electrode) can be paired with other redox couples to form novel flow batteries (FBs). As an anolyte, the V(II)/V(III) redox couple can be paired with iron, manganese, cobalt, and cerium redox couples to form novel vanadium-iron (V-Fe), vanadium-manganese (V-Mn), vanadium-cobalt (V-Co), and vanadium-cerium (V-Ce) FBs, respectively. The V(IV)/V(V) redox couple as a catholyte can be coupled with hydrogen to form a vanadium hydrogen (V-H2) FB. In those new redox chemistries, redox reactions, energy density, round-trip efficiencies, crossover issues, and cell components (i.e., separator, ion exchange membrane, and electrode) are different from an all-vanadium flow battery discussed in previous chapters, and thus warrant a detailed discussion.
The increasing use of renewable energy sources is leading to increased cycling of fossil-fueled power plants (FFPP) that are designed to operate at base-loaded conditions. Integrating energy storage facilities with the FFPPs can be helpful in reducing load-following operation of FFPPs. Decentralized deployment of energy storage facilities at the FFPP level has considerable advantages due to possibilities of smaller storage capacities, immediate benefits realized by the host power plant due to the increase in the efficiency, cleaner emission and higher plant life to name a few. Most importantly, deployment at the FFPP level can exploit the existing equipment items and facilities at the host power plant, thus reducing the CAPEX and reducing the storage capacity. However, realization of these benefits will critically depend on novel configuration/integration strategies with the least impact on the power plant operation and its configuration. Furthermore, dynamics of the entire integrated system including both the FFPP and the storage technologies must be taken into account to obtain the cost-optimal solution. With these motivations, the objective of this project was to complete a focused evaluation of decentralized deployments of energy storage facilities at the FFPP level. Promising thermal, chemical, mechanical, and electro-chemical storage technologies were evaluated with due consideration of their transient response to obtain various optimal system concepts that can minimize the levelized cost of storage. For thermal storage, cryogenic energy storage along with high temperature heat storage in molten salt as well as phase change material were evaluated. For mechanical storage, cryogenic air storage and pumped hydro storages were evaluated. For chemical storage, hydrogen storage was evaluated. For electrochemical storage, the team evaluated sodium sulfur, vanadium redox flow battery as well as Li-ion batteries. Integration of these storage technologies with the natural gas combined cycle (NGCC) and supercritical pulverized coal (SCPC) plants was considered. Six technologies, namely molten salt, cryogenics, compressed air, pumped hydro, H2 storage and Li-ion battery storage, were downselected based on their levelized cost of storage. It was observed that the ranking of the optimal storage technology can differ based on the host power plant technology even when same demand/supply/price profile for electricity are considered. It was also observed that as the variability in power demand varies, the ranking of the optimal storage technologies vary. However, for the same demand and LMP profile, top six optimal storage technologies for NGCC vs SCPC plants did not differ much even though LCOS for the same technology and optimal size of a given storage technology did differ. Detailed techno-economic assessment of these six technologies was undertaken.
This research aims to advance the field of vanadium redox flow batteries (VRFBs) by introducing a pioneering approach to optimize the microstructural characteristics of carbon cloth electrodes.
Redox flow batteries are considered a promising technology for grid energy storage. However, capacity decay caused by crossover of active materials is a universal challenge for many flow battery systems, which are based on various chemistries. In this paper, using the vanadium redox flow battery as an example, we demonstrate a new gel polymer interface (GPI) consisting of crosslinked polyethyleneimine with a large amount of amino and carboxylic acid groups introduced between the positive electrode and the membrane. The GPI functions as a key component to prevent vanadium ions from crossing the membrane, thus supporting stable long-term cycling. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements were conducted to investigate the effect of GPI on the electrochemical properties of graphitic carbon electrodes (GCFs) and redox reaction of catholyte. X-ray photoelectron spectroscopy (XPS) and 1 H nuclear magnetic resonance (NMR) spectra demonstrated that the crosslinked GPI is chemically stable for 100 cycles without dissolution of polymers and swelling in the strong acidic electrolytes. Results from inductively coupled plasma mass spectrometry (ICP-MS), Fourier-transform infrared (FTIR) spectroscopy, and energy-dispersive X-ray (EDX) spectroscopy proved that the GPI is effective in maintaining the concentration of vanadium species in their respective half-cells, resulting in improved cycling stability because of it prevents active species from crossing the membrane and stabilizes the oxidation states of active species.
The effect of surfactant additives on electrochemical behavior in porous electrodes was investigated using vanadium redox flow battery half-cells and the dependence of volumetric kinetics and mass transport on electrolyte, surfactant, and electrode type was explored. Without surfactant added, carbon paper electrodes demonstrated greater kinetics and transport compared to carbon felt, for a given electrolyte. Additionally, posolyte kinetics are greater than negolyte kinetics by one to three orders of magnitude, depending on the electrode type. Addition of surfactant increased electrode wettability and possibly electrochemical surface area. However, this was accompanied by a decrease in volumetric mass transport, due to stronger electrolyte-electrode interactions. The presence of sodium dodecyl sulfate (SDS) influenced posolyte and negolyte kinetics differently. Kinetics showed a dependence on electrode type and surfactant. On carbon felt, volumetric kinetics decreased for both posolyte and negolyte with SDS addition. On carbon paper, SDS decreased volumetric kinetics for the posolyte but increased (>2X) kinetics for the negolyte! This kinetic enhancement depends on surfactant chemistry: cetyltrimethylammonium bromide, a cationic surfactant, failed to increase kinetics. Furthermore, SDS did not increase areal specific resistance. Furthermore, these findings show the superior performance of carbon paper compared to carbon felt and suggest SDS as a possible VRFB negolyte additive.
Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.
Here, in this paper, we present a physics-constrained deep neural network (PCDNN) method for parameter estimation in the zero-dimensional (0D) model of the vanadium redox flow battery (VRFB). In this approach, we use deep neural networks to approximate the model parameters as functions of the operating conditions. This method allows the integration of VRFB computational models as the physical constraints in the parameter learning process, leading to enhanced accuracy of parameter estimation and cell voltage prediction. Using an experimental dataset, we demonstrate that the PCDNN method can estimate model parameters for a range of operating conditions and improve the 0D model prediction of voltage compared to the 0D model prediction with constant operation-condition-independent parameters estimated with traditional inverse methods. We also demonstrate that the PCDNN approach has an improved generalization ability for estimating parameter values for operating conditions not used in the training process.
A fluoro sulfonated poly(phenylene) was rationally designed with an external hydrophobic shell and internal hydrophilic core in order to improve the durability and ion selectivity of a hydrocarbon membrane for vanadium redox flow batteries (VRFBs). The polymer was designed to prevent hydrophilic polymer chain aggregation by attaching acid moieties onto the polymer backbone, while functionalizing the external polymer shell with hydrophobic side chains to prevent excessive vanadium crossover associated with cation exchange membranes. As an example, the hydrophobic shell can be provided by pentafluorobenzoyl group functionalization of the pendent aryl groups on a Diels Alder poly(phenylene) backbone, while the internal polymer chain can contain sulfonic acid moieties to impart hydrophilic character.
This paper presents a novel technique for generating a convex system model from an experimentally derived data set which features variance among repeated measurements. The convex system model developed as a test case characterizes the dynamic system losses of a vanadium redox flow battery as a function of the active power output and the battery state of charge. The technique hinges on a pre-cleaning via clustering procedure which precedes the formation of a planar convex hull comprised of triangular simplices. The clustering procedure efficiently reduces the experimental data set while mitigating variance among repeated measurements and removes outliers. Ultimately, the lower evelope of the planar convex hull serves as the desired convex system model. The proposed technique reduces systematic model error which is otherwise present when directly developing a planar convex hull model based on an unreduced data set.
In this paper, we present a physics-informed neural network (PINN) approach for predicting the performance of an all-vanadium redox flow battery, with its physics constraints enforced by a two-dimensional (2D) mathematical model. The 2D model, which includes 6 governing equations and 24 boundary conditions, provides a detailed representation of the electrochemical reactions, mass transport and hydrodynamics occurring inside the redox flow battery. To solve the 2D model with the PINN approach, a composite neural network is employed to approximate species concentration and potentials; the input and output are normalized according to prior knowledge of the battery system; the governing equations and boundary conditions are first scaled to an order of magnitude around 1, and then further balanced with a self-weighting method. Our numerical results show that the PINN is able to predict cell voltage correctly, but the prediction of potentials shows a constant-like shift. To fix the shift, the PINN is enhanced by further constrains derived from the current collector boundary. Finally, we show that the enhanced PINN can be even further improved if a small number of labeled data is available.
This study presents a comprehensive techno-economic characterization of energy storage and exible low carbon power generation technologies that can shift energy across days, weeks, or months to balance daily, weekly, and seasonal disparities in supply and demand. Energy storage technologies evaluated here include pumped hydropower storage (PHS), adiabatic and diabatic compressed air energy storage (CAES), vanadium redox flow batteries (VRBs), pumped thermal energy storage (P-TES), and renewably produced hydrogen stored in either geologic formations or underground pipes with re-electrification via combustion turbines in combined cycles, stationary proton exchange membrane (PEM) fuel cells, or the novel use of PEM fuel cells designed for heavy-duty vehicles (HDVs) which are expected to have shorter lives but also lower capital costs. We also evaluate flexible low-carbon power generation systems, including ethanol combustion in gas turbines and natural gas combustion with carbon capture and sequestration (CCS). We estimate current costs with literature data, use learning rates to characterize future costs, and develop capacity factors calibrated to an 85% renewables grid to calculate the levelized cost of energy (LCOE) of each technology. Results illustrate that at the 12-hour storage duration, PHS and CAES have the lowest LCOE with current costs, and VRBs become competitive if future costs are achieved. At the 120-hour storage duration, hydrogen systems with geologic storage and natural gas with CCS achieve the lowest LCOE in both current and future capital cost scenarios. In particular, the new configuration of HDV-PEM fuel cells with hydrogen storage in geologic formations evaluated here could lower the LCOE by 22-27% compared to stationary fuel cell systems typically evaluated and might help enable very high (>80%) renewable energy electric power systems. P-TES and hydrogen stored in underground pipes are the least-cost options at the 120-hour storage duration rating that do not require some form of geologic storage. Sensitivity analysis and Monte Carlo analysis illustrate that the general trends seen in this study are valid for a wide range of capacity factors and future cost scenarios. The study also illustrates that coproducing and selling hydrogen to other markets could reduce the LCOE of hydrogen systems by up to 39%.
The objective of the proposed project is to develop and demonstrate an ultra-stable reference electrode (RE) technology as an in-situ system diagnostics tool integrated in kW scaled commercial vanadium redox flow battery (VRFB) stacks for long-duration energy storage (LDES) applications and to advance its commercialization, with expected cell reliability enhancement in stack life increase of 6-10 % and levelized cost of storage (LCOS) reduction of 5-8 %. In this project, PNNL will partner with Stryten Energy LLC, with a total budget of $250K and 50% cost share for one year.