Battery lifetime of electric vehicles by novel rainflow-counting algorithm with temperature and C-rate dynamics: Effects of fast charging, user habits, vehicle-to-grid and climate zones

The adoption of electric vehicles is expected to soon widespread to cope with energy transition needs; however, concerns on battery lifetime arise, especially related to charging behaviors, vehicle usage habits, vehicle-to -grid and weather conditions. In fact, lifetime battery modeling is a challenging dynamic to characterize, as it involves complex chemical processes related to charging, discharging and temperature dynamics over long time spans that are often difficult to dominate, given the large uncertainties. Having a fatigue-like behavior, the battery aging has sometimes been modeled using rainflow-counting algorithms, yet traditional modeling is not holistic and approximations are used, especially when considering temperature or current dynamics. Based on experimental data, this paper aims at developing a holistic battery degradation model based on rainflow-counting algorithm to properly account for all major determinants of capacity loss, namely cycling usage, calendar lifetime, dynamic temperature and battery current. The approach is coupled with a physical-electro-thermal modeling of the vehicle system, developed in Modelica language, to accurately simulate the intertwined thermal and electrical behavior of the system subject to different usage charging behaviors, including slow and fast charging, as well as vehicle-to-grid application. The proposed case study shows the expected lifetime of electric vehicles to be comparable with of traditional cars (10-20y) and that the proposed temperature -dependent battery modeling enables reducing estimation errors up to 27%. A sensitivity on different climate zones has been considered and results suggest that cool climates can increase life expectancy by 30% with respect to hot climates in typical Italian contexts

Sistemi di accumulo "in energia" e "in potenza" a beneficio delle reti elettriche

L’articolo descrive una serie di applicazioni che i sistemi di accumulo di energia possono svolgere a beneficio dell’esercizio del sistema elettrico e dell’efficienza delle reti elettriche. Sono confrontate le principali tipologie di sistemi di accumulo elettrochimico, attraverso parametri prestazionali tipici della tecnologia

Optimal sizing of residential battery systems with multi-year dynamics and a novel rainflow-based model of storage degradation: An extensive Italian case study

Residential battery storage to perform load shifting and demand side management has become of utmost importance to improve hosting capacity, increase renewable energy penetration and meet environmental targets, especially with energy community policies. As the lifetime of electrochemical batteries depends upon their scheduling and environmental conditions, the multi-year effects of operational strategies can affect the economics of the investment. However, rarely complete long-term simulations of the operation of storage systems are performed to assess the battery profitability including the operational effects of aging, and limited studies account for a large statistics of consumers. In this study, we propose a multi-year sizing methodology for residential applications, where the complete lifetime of batteries is simulated at 15-min time resolution till complete degradation using an improved non-linear non-convex degradation model; the photovoltaic plant aging is also considered. An extensive analysis on the economics and commercial size best suited for 399 real load profiles in Italy is proposed. Results suggest that the break-even price of the storage is about 400 €/kWh, which is lower than the average commercial price, and that, as reviewed, current market components may be unfit for consumers with low energy demand. Net Present Value (NPV) and Discounted PayBack Time (DPBT) can reach 500-1500 € and 8-11 years

An energy resource scheduler implemented in the automatic management system of a microgrid test facility

The paper deals with a microgrid test facility, settled at the CESI RICERCA laboratories, equipped with various distributed energy resources (DERs) and connected to a LV network. The operation of such a microgrid is supervised by a central automatic microgrid management system (MMS). The paper first reports and discusses some experimental results carried out for the assessment of DERs performance and for the implementation of specific MMS functions. Then, it describes the functions of the energy resources scheduler (ERS) implemented in the MMS. The scheduler periodically updates the set points of DERs regulators in order to achieve economic, reliability and power quality objectives, starting form the load and renewable production forecasts and from the results of the system state estimation. The ERS is composed by two main parts, namely: a day-ahead economic scheduler of active power set points during the following day for the minimization of the overall costs, and an intra-day scheduler that every 15 minutes settles the set points of the DERs regulators to optimize the voltage profile at the grid buses, taking into account both technical constraints and the day-ahead economic schedules. © 2007 IEEE

An Energy Resource Scheduler Implemented in the Automatic Management System of a Microgrid Test Facility

The paper deals with a microgrid test facility, settled at the CESI RICERCA laboratories, equipped with various distributed energy resources (DERs) and connected to a LV network. The operation of such a microgrid is supervised by a central automatic microgrid management system (MMS). The paper first reports and discusses some experimental results carried out for the assessment of DERs performance and for the implementation of specific MMS functions. Then, it describes the functions of the energy resources scheduler (ERS) implemented in the MMS. The scheduler periodically updates the set points of DERs regulators in order to achieve economic, reliability and power quality objectives, starting form the load and renewable production forecasts and from the results of the system state estimation. The ERS is composed by two main parts, namely: a day-ahead economic scheduler of active power set points during the following day for the minimization of the overall costs, and an intra-day scheduler that every 15 minutes settles the set points of the DERs regulators to optimize the voltage profile at the grid buses, taking into account both technical constraints and the day-ahead economic schedules

Group A rotavirus surveillance before vaccine introduction in Italy, September 2014 to August 2017.

IntroductionGroup A rotaviruses (RVA) are the leading cause of acute gastroenteritis (AGE) in young children, causing ca 250,000 deaths worldwide, mainly in low-income countries. Two proteins, VP7 (glycoprotein, G genotype) and VP4 (protease-sensitive protein, P genotype), are the basis for the binary RVA nomenclature. Although 36 G types and 51 P types are presently known, most RVA infections in humans worldwide are related to five G/P combinations: G1P[8], G2P[4], G3P[8], G4P[8], G9P[8].AimThis study aimed to characterise the RVA strains circulating in Italy in the pre-vaccination era, to define the trends of circulation of genotypes in the Italian paediatric population.MethodsBetween September 2014 and August 2017, after routine screening in hospital by commercial antigen detection kit, 2,202 rotavirus-positive samples were collected in Italy from children hospitalised with AGE; the viruses were genotyped following standard European protocols.ResultsThis 3-year study revealed an overall predominance of the G12P[8] genotype (544 of 2,202 cases; 24.70%), followed by G9P[8] (535/2,202; 24.30%), G1P[8] (459/2,202; 20.84%) and G4P[8] (371/2,202; 16.85%). G2P[4] and G3P[8] genotypes were detected at low rates (3.32% and 3.09%, respectively). Mixed infections accounted for 6.49% of cases (143/2,202), uncommon RVA strains for 0.41% of cases (9/2,202).ConclusionsThe emergence of G12P[8] rotavirus in Italy, as in other countries, marks this genotype as the sixth most common human genotype. Continuous surveillance of RVA strains and monitoring of circulating genotypes are important for a better understanding of rotavirus evolution and genotype distribution, particularly regarding strains that may emerge from reassortment events

Group A rotavirus surveillance before vaccine introduction in Italy, September 2014 to August 2017.

Abstract IntroductionGroup A rotaviruses (RVA) are the leading cause of acute gastroenteritis (AGE) in young children, causing ca 250,000 deaths worldwide, mainly in low-income countries. Two proteins, VP7 (glycoprotein, G genotype) and VP4 (protease-sensitive protein, P genotype), are the basis for the binary RVA nomenclature. Although 36 G types and 51 P types are presently known, most RVA infections in humans worldwide are related to five G/P combinations: G1P[8], G2P[4], G3P[8], G4P[8], G9P[8].AimThis study aimed to characterise the RVA strains circulating in Italy in the pre-vaccination era, to define the trends of circulation of genotypes in the Italian paediatric population.MethodsBetween September 2014 and August 2017, after routine screening in hospital by commercial antigen detection kit, 2,202 rotavirus-positive samples were collected in Italy from children hospitalised with AGE; the viruses were genotyped following standard European protocols.ResultsThis 3-year study revealed an overall predominance of the G12P[8] genotype (544 of 2,202 cases; 24.70%), followed by G9P[8] (535/2,202; 24.30%), G1P[8] (459/2,202; 20.84%) and G4P[8] (371/2,202; 16.85%). G2P[4] and G3P[8] genotypes were detected at low rates (3.32% and 3.09%, respectively). Mixed infections accounted for 6.49% of cases (143/2,202), uncommon RVA strains for 0.41% of cases (9/2,202).ConclusionsThe emergence of G12P[8] rotavirus in Italy, as in other countries, marks this genotype as the sixth most common human genotype. Continuous surveillance of RVA strains and monitoring of circulating genotypes are important for a better understanding of rotavirus evolution and genotype distribution, particularly regarding strains that may emerge from reassortment event