A realistic model for battery state of charge prediction in energy management simulation tools

In this paper, a comprehensive model for the prediction of the state of charge of a battery is presented. This model has been specifically designed to be used in simulation tools for energy management in (smart) grids. Hence, this model is a compromise between simplicity, accuracy and broad applicability. The model is verified using measurements on three types of Lead-acid (Pb-acid) batteries, a Lithium-ion Polymer (Li-Poly) battery and a Lithium Iron-phosphate (LiFePo) battery. For the Pb-acid batteries the state of charge is predicted for typical scenarios, and these predictions are compared to measurements on the Pb-acid batteries and to predictions made using the KiBaM model. The results show that it is possible to accurately model the state of charge of these batteries, where the difference between the model and the state of charge calculated from measurements is less than 5%. Similarly the model is used to predict the state of charge of Li-Poly and LiFePo batteries in typical scenarios. These predictions are compared to the state of charge calculated from measurements, and it is shown that it is also possible to accurately model the state of charge of both Li-Poly and LiFePo batteries. In the case of the Li-Poly battery the difference between the measured and predicted state of charge is less than 5% and in the case of the LiFePo battery this difference is less than 3%

A comprehensive model for battery State of Charge prediction

In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data. The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations

The natural history of primary sclerosing cholangitis in 781 children. A multicenter, international collaboration

There are limited data on the natural history of primary sclerosing cholangitis (PSC) in children. We aimed to describe the disease characteristics and long-term outcomes of pediatric PSC. We retrospectively collected all pediatric PSC cases from 36 participating institutions and conducted a survival analysis from the date of PSC diagnosis to dates of diagnosis of portal hypertensive or biliary complications, cholangiocarcinoma, liver transplantation, or death. We analyzed patients grouped by disease phenotype and laboratory studies at diagnosis to identify objective predictors of long-term outcome. We identified 781 patients, median age 12 years, with 4,277 person-years of follow-up; 33% with autoimmune hepatitis, 76% with inflammatory bowel disease, and 13% with small duct PSC. Portal hypertensive and biliary complications developed in 38% and 25%, respectively, after 10 years of disease. Once these complications developed, median survival with native liver was 2.8 and 3.5 years, respectively. Cholangiocarcinoma occurred in 1%. Overall event-free survival was 70% at 5 years and 53% at 10 years. Patient groups with the most elevated total bilirubin, gamma-glutamyltransferase, and aspartate aminotransferase-to-platelet ratio index at diagnosis had the worst outcomes. In multivariate analysis PSC-inflammatory bowel disease and small duct phenotypes were associated with favorable prognosis (hazard ratios 0.6, 95% confidence interval 0.5-0.9, and 0.7, 95% confidence interval 0.5-0.96, respectively). Age, gender, and autoimmune hepatitis overlap did not impact long-term outcome. CONCLUSION: PSC has a chronic, progressive course in children, and nearly half of patients develop an adverse liver outcome after 10 years of disease; elevations in bilirubin, gamma-glutamyltransferase, and aspartate aminotransferase-to-platelet ratio index at diagnosis can identify patients at highest risk; small duct PSC and PSC-inflammatory bowel disease are more favorable disease phenotypes

Assessing the Validity of Adult-derived Prognostic Models for Primary Sclerosing Cholangitis Outcomes in Children

Background: Natural history models for primary sclerosing cholangitis (PSC) are derived from adult patient data, but have never been validated in children. It is unclear how accurate such models are for children with PSC. Methods: We utilized the pediatric PSC consortium database to assess the Revised Mayo Clinic, Amsterdam-Oxford, and Boberg models. We calculated the risk stratum and predicted survival for each patient within each model using patient data at PSC diagnosis, and compared it with observed survival. We evaluated model fit using the c-statistic. Results: Model fit was good at 1 year (c-statistics 0.93, 0.87, 0.82) and fair at 10 years (0.78, 0.75, 0.69) in the Mayo, Boberg, and Amsterdam-Oxford models, respectively. The Mayo model correctly classified most children as low risk, whereas the Amsterdam-Oxford model incorrectly classified most as high risk. All of the models underestimated survival of patients classified as high risk. Albumin, bilirubin, AST, and platelets were most associated with outcomes. Autoimmune hepatitis was more prevalent in higher risk groups, and over-weighting of AST in these patients accounted for the observed versus predicted survival discrepancy. Conclusions: All 3 models offered good short-term discrimination of outcomes but only fair long-term discrimination. None of the models account for the high prevalence of features of autoimmune hepatitis overlap in children and the associated elevated aminotransferases. A pediatric-specific model is needed. AST, bilirubin, albumin, and platelets will be important predictors, but must be weighted to account for the unique features of PSC in children.Peer reviewe

Daphnia parasite dynamics across multiple Caullerya epidemics indicate selection against common parasite genotypes

Studies of parasite population dynamics in natural systems are crucial for our understanding of host–parasite coevolutionary processes. Some field studies have reported that host genotype frequencies in natural populations change over time according to parasite-driven negative frequency-dependent selection. However, the temporal patterns of parasite genotypes have rarely been investigated. Moreover, parasite-driven negative frequency-dependent selection is contingent on the existence of genetic specificity between hosts and parasites. In the present study, the population dynamics and host-genotype specificity of the ichthyosporean Caullerya mesnili, a common endoparasite of Daphnia water fleas, were analysed based on the observed sequence variation in the first internal transcribed spacer (ITS1) of the ribosomal DNA. The Daphnia population of lake Greifensee (Switzerland) was sampled and subjected to parasite screening and host genotyping during C. mesnili epidemics of four consecutive years. The ITS1 of wild-caught C. mesnili-infected Daphnia was sequenced using the 454 pyrosequencing platform. The relative frequencies of C. mesnili ITS1 sequences differed significantly among years: the most abundant C. mesnili ITS1 sequence decreased and rare sequences increased over the course of the study, a pattern consistent with negative frequency-dependent selection. However, only a weak signal of host-genotype specificity between C. mesnili and Daphnia genotypes was detected. Use of cutting edge genomic techniques will allow further investigation of the underlying micro-evolutionary relationships within the Daphnia–C. mesnili system

Bone Material Properties in Osteogenesis Imperfecta

Osteogenesis imperfecta entrains changes at every level in bone tissue, from the disorganisation of the collagen molecules and mineral platelets within and between collagen fibrils, to the macro-architecture of the whole skeleton. Investigations using an array of sophisticated instruments at multiple scale levels have now determined many aspects of the effect of the disease on the material properties of bone tissue. The brittle nature of bone in osteogenesis imperfecta reflects both increased bone mineralisation density – the quantity of mineral in relation to the quantity of matrix within a specific bone volume – and altered matrix-matrix and matrix mineral interactions. Contributions to fracture resistance at multiple scale lengths are discussed, comparing normal and brittle bone. Integrating the available information provides both a better understanding of the effect of current approaches to treatment – largely improved architecture and possibly some macro-scale toughening - and indicates potential opportunities for alternative strategies that can influence fracture resistance at longer length scales

Batteries in Smart Microgrids

To counter the effects of global climate change, attributed to the CO2 emissions resulting from burning fossil fuels for generating electricity and heat, global efforts are being made to achieve an energy transition. This includes that the share of energy generated using sustainable sources (e.g. solar, wind, hydro) should be increased, while the share of energy generated using fossil sources (e.g. natural gas, coal, oil) should be decreased, ultimately phasing out the usage of fossil fuels altogether. How this energy transition should be achieved, or even when the energy transition should be completed is subject of heated debates in political arenas, courts of law and the society as a whole. Whether or not future electricity demands can be met by sustainable sources is a particular important part of this debate. On the one hand, fossil fuels are ( for the moment) cheap and readily available, by using fossil fuels it is always possible to generate the appropriate amount of electricity to match the demand. On the other hand, generating electricity from sunlight or wind can only be done when enough sun- light is available or the wind-speed is in an appropriate bandwidth. However, as electricity is also used during the night, and on cloudy, windless or stormy days, using sustainable energy sources as the primary supply for electricity generation can lead to a significant mismatch between supply and demand. This can imply that sometimes the electricity generated by solar parks during the day has to be curtailed because there is no demand for it, while during the night electricity still has to be generated using fossil fuels to meet the demand. A solution to this problem seems obvious: store the electricity. This allows to generate electricity using sustainable sources when available, and to store a sufficient amount to be able to meet the demand at all times. Although, this solution sounds simple, still many questions remain. Which type of storage should be used?, Where should the storage be located?, What should be the capacity of the storage?, How should the storage be used?, etc. In this thesis these types of questions are addressed for a specific type of storage: batteries. To answer these questions, and to support the important decisions necessary to complete the energy transition, three contributions are made: The first contribution is the development of the diffusion buffer model (DiBu- model) for battery state of charge (SoC) prediction. This model is specifically designed to be used in simulation tools for energy management in (smart) grids. Hence, this model should be a consolidation of broad applicability, accuracy and simplicity. The broad applicability of the DiBu-model is demonstrated by accurate predictions of the SoC of Lead-acid, Lithium-ion Polymer and Lithium Iron-phosphate batteries under various scenarios. The accuracy of the model is demonstrated by comparing the predicted SoC for various scenarios to the SoC calculated from measurements on real batteries subjected to these scenarios. The results show that it is possible to accurately predict the SoC for these types of batteries using the DiBu-model, where the difference between the predicted SoC and the SoC calculated from measurements is generally less than 5%. The broad applicability and accuracy are also demonstrated by accurate SoC predictions on an experimental Seasalt battery, although a slight modification to the model was necessary in this case. The simplicity is demonstrated by integrating the DiBu-model in the DEMKit smart grid energy management toolkit. Here the results show that by using the DiBu-model more realistic predictions of the SoC can be made, compared to an idealized battery model used previously. The integration of the model in DEMKit is validated by comparing the SoC predicted using DEMKit to the SoC derived from measurements on an actual battery. The difference between the predicted and measured SoC is generally less than 1.5%. The second contribution is the so called "16 houses case" in which the integration of batteries in a smart microgrid is considered. More specifically the possibilities of "soft-islanding" ( near autarkic behaviour) a microgrid with 16 houses is in- vestigated. The research is focussed on an idealised "greenfield" neighbourhood where energy is generated by PV-panels as well as by a CHP and energy is stored using batteries as well as a heat buffer. Firstly, a proper sizing of the equipment is determined based on energy production and consumption data of several weeks spread over the year. Secondly, one year simulations for several scenarios are presented and the degree of autarky ( DoA) for each scenario is compared. It is demonstrated that a (nearly) autarkic operating microgrid can be achieved by combining the proper sizing of energy generation and storage assets, with an advanced control. It is possible to achieve a DoA of 99.1% over a year, meaning that less than one percent of the energy has to be imported from the main grid. Subsequently the tools and methods used for the ideal neighbourhood are applied in a case study of a real neighbourhood: Markluiden. For this neighbourhood it is possible to reach a DoA of around 91% over a year. The third contribution concerns the Seasalt battery, a novel battery currently under development at Dr Ten B.V. The Seasalt battery is particularly suitable for stationary use, e.g. as a home or neighbourhood battery. In that role it is an alternative to e.g. Lead-acid and Lithium-ion Polymer batteries. A detailed description of the battery and it’s behaviour is given, in addition to a discussion of it’s advantages and disadvantages. The advantages include the usage of environ- mentally friendly and (where possible) sustainable materials in it’s construction, and limited risks to health and safety compared to Lead-acid and Lithium-ion Polymer batteries. Disadvantages include a lower capacity / weight and capacity / volume ratio in comparison with the aforementioned batteries. Furthermore, examples of real-world application of the Seasalt battery are discussed. Finally, the prevention of dendrites forming at the anode of the Seasalt battery, which was a particularly challenging aspect of the battery design, is discussed in detail