Behavior-oriented Modeling of Electric Vehicle Load Profiles: A Stochastic Simulation Model Considering Different Household Characteristics, Charging Decisions and Locations

This paper presents a stochastic bottom-up model to assess electric vehicles\u27 (EV) impact on load profiles at different parking locations as well as their load management potential assuming different charging strategies. The central innovation lies in theconsideration of socio-economic, technical and spatial factors, all of which influence charging behavior and location. Based on a detailed statistical analysis of a large dataset on German mobility, the most statistically significant influencing factors on residential charging behavior could be identified. Whilst household type and economic status are the most important factors for the number of cars per household, the driver\u27s occupation has the strongest influence on the first departure time and parking time whilst at work. An inhomogeneous Markov-chain is used to sample a sequence of destinations of each car trip, depending (amongst other factors) on the occupation of the driver, the weekday and the time of the day. Probability distributions for the driven kilometres, driving durations and parking durations are used to derive times and electricity demand. The probability distributions are retrieved from a national mobility dataset of 70,000 car trips and filtered for a set of socio-economic and demographic factors. Individual charging behaviour is included in the model using a logistic function accounting for the sensitivity of the driver towards (low) battery SOC. The presented model is validated with this mobility dataset and shown to have a deviation in key household mobility characteristics of just a few percentage points. The model is then employed to analyse the impact of uncontrolled charging of BEV on the residential load profile. It is found that the absolute load peaks will increase by up to factor 8.5 depending on the loading infrastructure, the load in high load hours will increase by approx. a factor of 3 and annual electricity demand will approximately double

Urinary NMR Profiling in Pediatric Acute Kidney Injury—A Pilot Study

Acute kidney injury (AKI) in critically ill children and adults is associated with significant short- and long-term morbidity and mortality. As serum creatinine- and urine output-based definitions of AKI have relevant limitations, there is a persistent need for better diagnostics of AKI. Nuclear magnetic resonance (NMR) spectroscopy allows for analysis of metabolic profiles without extensive sample manipulations. In the study reported here, we examined the diagnostic accuracy of NMR urine metabolite patterns for the diagnosis of neonatal and pediatric AKI according to the Kidney Disease: Improving Global Outcomes (KDIGO) definition. A cohort of 65 neonatal and pediatric patients (0–18 years) with established AKI of heterogeneous etiology was compared to both a group of apparently healthy children (n = 53) and a group of critically ill children without AKI (n = 31). Multivariate analysis identified a panel of four metabolites that allowed diagnosis of AKI with an area under the receiver operating characteristics curve (AUC-ROC) of 0.95 (95% confidence interval 0.86–1.00). Especially urinary citrate levels were significantly reduced whereas leucine and valine levels were elevated. Metabolomic differentiation of AKI causes appeared promising but these results need to be validated in larger studies. In conclusion, this study shows that NMR spectroscopy yields high diagnostic accuracy for AKI in pediatric patients

Advanced Bifunctional Oxygen Reduction and Evolution Electrocatalyst Derived from Surface-Mounted Metal-Organic Frameworks

Metal‐organic frameworks (MOFs) and their derivatives are considered as promising catalysts for the oxygen reduction (ORR) and oxygen evolution reaction (OER), which are important for many energy provision technologies, such as electrolyzers, fuel cells and some types of advanced batteries. In this work, a “strain modulation” approach has been applied through the use of surface‐mounted NiFe‐MOFs in order to design an advanced bifunctional ORR/OER electrocatalyst. The material exhibits an excellent OER activity in alkaline media, reaching an industrially relevant current density of 200 mA·cm ‐2 at an overpotential of just ~210 mV. It demonstrates operational long‐term stability even at a high current density of 500 mA·cm ‐2 and exhibits the so far narrowest “overpotential window” ΔE ORR‐OER : 0.69 V in 0.1 M KOH with a mass loading being two orders of magnitude lower than that of benchmark electrocatalysts

A practical perspective on the potential of rechargeable Mg batteries

Emerging energy storage systems based on abundant and cost-effective materials are key to overcome the global energy and climate crisis of the 21st century. Rechargeable Magnesium Batteries (RMB), based on Earth-abundant magnesium, can provide a cheap and environmentally responsible alternative to the benchmark Li-ion technology, especially for large energy storage applications. Currently, RMB technology is the subject of intense research efforts at laboratory scale. However, these emerging approaches must be placed in a real-world perspective to ensure that they satisfy key technological requirements. In an attempt to bridge the gap between laboratory advancements and industrial development demands, herein, we report the first non-aqueous multilayer RMB pouch cell prototypes and propose a roadmap for a new advanced RMB chemistry. Through this work, we aim to show the great unrealized potential of RMBs.This work was funded by European Union's Horizon 2020 research and innovation program under the FET Proactive call with grant agreement no 824066 via the “E-MAGIC” project

A practical perspective on the potential of rechargeable Mg batteries

Emerging energy storage systems based on abundant and cost-effective materials are key to overcome the global energy and climate crisis of the 21st century. Rechargeable Magnesium Batteries (RMB), based on Earth-abundant magnesium, can provide a cheap and environmentally responsible alternative to the benchmark Li-ion technology, especially for large energy storage applications. Currently, RMB technology is the subject of intense research efforts at laboratory scale. However, these emerging approaches must be placed in a real-world perspective to ensure that they satisfy key technological requirements. In an attempt to bridge the gap between laboratory advancements and industrial development demands, herein, we report the first non-aqueous multilayer RMB pouch cell prototypes and propose a roadmap for a new advanced RMB chemistry. Through this work, we aim to show the great unrealized potential of RMBs