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Sodium-ion (Na-ion) batteries are touted as the next generation alternative to lithium-ion (Li-ion) batteries as the elemental abundance of sodium addresses the supply risks in the Li-ion supply chain. Numerous studies have been carried out on the design of Li-ion batteries for energy, power, and cost, but analogous work has yet to be performed for Na-ion batteries. In this work, we demonstrated the energy, power, and cost-optimization of a hard‑carbon – sodium vanadium fluorophosphate Na-ion battery via a novel approach that combines physics-based and cost models. Energy and power densities are maximized using a multiphysics model, whereas material costs are minimized with Argonne National Laboratory's BatPac model. Both models are applied by finding the electrode thicknesses and porosities that optimizes their objective functions. The optimized Na-ion batteries are benchmarked with the commercially mature Li-ion lithium iron phosphate and nickel manganese cobalt oxide chemistries. Optimization with the physics-based model reveals that energy cells have thick and low porosity electrodes, while power cells have thin and high porosity electrodes. The cost-optimized Na-ion batteries had similar design parameters as energy cells to minimize the per-kWh material costs. The results therefore demonstrate a tradeoff between designing a battery for energy and cost versus power. The energy and cost-optimized Na-ion batteries have lower energy densities and higher costs than Li-ion batteries, although these characteristics may still be enhanced. The energy densities of Na-ion batteries may be bolstered with improvements in materials science, whereas the costs of Na-ion batteries can be driven down with increased economies of scale.

•Carbon Nanofibers were dispersed in water with a mix of organic expanders.•The dispersions were added to different negative plates and 2 V/1 Ah cells were built.•These fibers are thought to be integrated in the NAM skeleton.•Organic expanders were essential for the cell capacity and the cold cranking ability.•Carbon Nanofibers improved the cycling performance compared to our reference.

Batteries are pivotal towards the decarbonization of energy systems as they address the intermittent nature of renewable energy technologies. The techno-economic feasibility of deploying batteries in microgrids is often analyzed using energy systems modeling tools. These often utilize the idealized battery model, which is simpler but neglects electrochemical phenomena. Reduced-order models, which are derived from continuum-scale physics-based models, have improved accuracy but are yet to be applied in the cost optimization of microgrids. In this work, we proposed a novel methodology for generating reduced-order models of lithium-ion lithium iron phosphate, nickel cobalt aluminum oxide, and nickel manganese cobalt chemistries for use in the techno-economic optimization of microgrids. We simulated previously reported multiphysics models of Li-ion batteries in COMSOL Multiphysics® and reduced them into equivalent circuit models. These were implemented in Island Systems LCOEminAlgorithm (ISLA), our in-house energy systems modeling and optimization tool. We then simulated and optimized renewable energy systems in ISLA to determine the discrepancy between the reduced-order equivalent circuit models versus the idealized battery model. The results revealed that the idealized battery model can miscalculate the SOC by >5 % SOC due to the assumption of constant voltages, while the optimum sizes differed by >5 % when there are sharp peaks in demand or if non-renewable sources are competitive. The idealized battery model is therefore not a valid approximation under these scenarios. This work demonstrated a novel multi-scale framework from the continuum-scale multiphysics modeling of batteries to macroscale energy systems optimization.

Different energy storage technologies can be potentially integrated into microgrids to support variable renewable energy generators. Long-duration flywheel energy storage is considered a new contender in the energy storage market. This energy storage technology has been previously evaluated in a techno-economic study, but it did not consider uncertainties in the model input data. In this work, stochastic techno-economic comparison is performed using microgrid modeling and Monte-Carlo methods to compare long-duration flywheels, lead-acid batteries and lithium-ion batteries for isolated microgrid and industrial facility. Results generally show a relatively high probability for long-duration flywheels to yield lower LCOS and LCOE compared to lithium-ion batteries in 2020. Higher probability can be attained when the overnight component cost of long-duration flywheels is reduced or when overnight diesel prices are high. However, the chances of long-duration flywheels yielding lower LCOS and LCOE rapidly decreases as time progresses. Long-duration flywheel manufacturers and promoters must find ways to accelerate price reduction by 2.5× from baseline to secure better chance of yielding a lower LCOS in 2050.

•This work provides a comprehensive review of the multiphysics modeling of lithium-ion, lead-acid, and vanadium redox flow batteries.•The electrochemical-thermal models of these battery chemistries, along with common extensions and modifications of these models, are discussed.•In future work, molecular-scale models can be used to build new multiphysics models and reconstruct transport property correlations based on first principles instead of empirical correlations.•Similarly, multiphysics models can be simplified via data reduction for use in battery monitoring and energy systems modeling.