Steady state load models for power system analysis

The last full review of load models used for power system studies occurred in the 1980s. Since then, new types of loads have been introduced and system load mix has changed considerably. The examples of newly introduced loads include drive-controlled motors, low energy consumption light sources and other modern power electronic loads. Their numbers have been steadily increasing in recent years, a trend which is expected to escalate. Accordingly, the majority of load models used in traditional power system studies are becoming outdated, as they are unable to accurately represent power demand characteristics of existing and future loads. Therefore, in order to accurately predict both active and non-active power demand characteristics of aggregated modern power system loads in different load sectors (e.g. residential, commercial or industrial), existing load models should be updated and new models developed. This thesis aims to fill this gap by developing individual, generic and aggregated steady state models of the most common loads in use today, as well as of those expected to show significant growth in the future. The component-based approach is adopted for load modelling, where individual load models are obtained in detailed simulations of physical devices. Whenever possible, the developed individual load models are validated by measurements. These detailed individual load models are then simplified and expressed as equivalent circuit and analytical models, which allowed the establishment of generic load models that can be easily aggregated. It should be noted that since all non-active power characteristics are correctly represented, the developed aggregated load models allow for a full harmonic analysis, which is not the case with the standard steady state load models. Therefore, the proposed load models form an extensive library of comprehensive load models that are suitable for use in multiple areas of power system research. Based on the results of research related to typical domestic/residential sector load mix, the newly developed load models are aggregated and then applied to a typical UK/Scotland distribution network. Considerable differences are seen between network characteristics of newly proposed and previously developed models. The voltage distortion of a typical distribution system bus is investigated, and it is shown that distortion of the system voltage is likely to increase significantly in the future. The results of the presented research also suggest that neglecting the harmonic characteristics from the set of general load attributes may introduce errors in standard load flow studies

Two cases of carbonic anhydrase va deficiency—an ultrarare metabolic decompensation syndrome presenting with hyperammonemia, lactic acidosis, ketonuria, and good clinical outcome

The combination of neonatal hyperammonemia, lactic acidosis, ketonuria, and hypoglycemia is pathognomonic for carbonic anhydrase VA (CA-VA) deficiency. We present two cases of this rare inborn error of metabolism. Both newborns with South Asian ancestry presented with a metabolic decompensation characterized by hyperammonemia, lactic acidosis and ketonuria; one also had hypoglycemia. Standard metabolic investigations (plasma amino acids, acylcarnitine profile, and urine organic acids) were not indicative of a specific organic aciduria or fatty acid oxidation defect but had some overlapping features with a urea cycle disorder (elevated glutamine, orotic acid, and low argi-nine). Hyperammonemia was treated initially with nitrogen scavenger therapy and carglumic acid. One patient required hemodialysis. Both have had a favorable long-term prognosis after their initial metabolic decompensation. Genetic testing confirmed the diagnosis of carbonic anhydrase VA (CA-VA) deficiency due to biallelic pathogenic variants in CA5A. These cases are in line with 15 cases previously described in the literature, making the phenotypic presentation pathognomonic for this ultrarare (potentially underdiagnosed) inborn error of metabolism with a good prognosis

Establishing data-intensive learning health systems: an interdisciplinary exploration of the planned introduction of hospital electronic prescribing and medicines administration systems in Scotland

Background Creating learning health systems, characterised by the use and repeated reuse of demographic, process and clinical data to improve the safety, quality and efficiency of care, is a key aim in realising the potential benefits and efficiency savings associated with the implementation of health information technology.Objectives We sought to investigate stakeholder perspectives on and experiences of the implementation of hospital electronic prescribing and medicines administration (HEPMA) systems in Scotland and use these to inform political decisions on approaches to promoting the use and reuse of digitised prescribing and medication administration data in order to improve care processes and outcomes.Methods We identified and recruited key national stakeholders involved in implementing and/or using HEPMA data from generic and specialty systems. These included representatives from healthcare settings (i.e. doctors, pharmacists and nurses), managers of existing national databases, policy makers, healthcare analytics companies, system suppliers and patient representatives. We conducted multi-disciplinary focus group discussions, audio-recorded these, transcribed data verbatim and thematically analysed the transcripts with the help of NVivo10. In analysing the data, we drew on theoretical and previous empirical work on information infrastructures.Results We identified the following key themes: 1) micro-factors – usability of systems and motivating users to input data; 2) meso-factors – developing technical and organisational infrastructures to facilitate the aggregation of data; and 3) macro-factors – facilitating interoperability and data reuse at larger scales to ensure that data are effectively generated and used.Conclusions This work is relevant not only to countries in the early stages of data strategy development but also to countries aiming to aggregate data at national levels. An overall shared vision of a learning health system at individual, organisational and national levels can help to catalyse such data-intensive transformational efforts

Structured oligo(aniline) nanofilms via ionic self-assembly

Conducting polymers have shown great potential for application in electronic devices. A major challenge in such applications is to control the supramolecular structures these materials form to optimise the functionality. In this work we probe the structure of oligo(aniline) thin films (of sub-μm thickness) drop cast on a silicon substrate using synchrotron surface diffraction. Self-assembly was induced through doping with an acid surfactant, bis(ethyl hexyl) phosphate (BEHP), resulting in the formation of well-ordered lamellae with the d-spacing ranging from 2.15 nm to 2.35 nm. The exact structural characteristics depended both on the oligomer chain length and film thickness, as well as the doping ratio. Complementary UV/Vis spectroscopy measurements confirm that such thin films retain their bulk electronic properties. Our results point to a simple and effective ionic self-assembly approach to prepare thin films with well-defined structures by tailoring parameters such as the oligomer molecular architecture, the nanofilm composition and the interfacial roughness

Qualitative analysis of multi-disciplinary round-table discussions on the acceleration of benefits and data analytics through hospital electronic prescribing (ePrescribing) systems

Background: Electronic systems that facilitate prescribing, administration and dispensing of medicines (ePrescribing systems) are at the heart of international efforts to improve the safety, quality and efficiency of medicine management. Considering the initial costs of procuring and maintaining ePrescribing systems, there is a need to better understand how to accelerate and maximise the financial benefits associated with these systems.Objectives: We sought to investigate how different sectors are approaching the realisation of returns on investment from ePrescribing systems in U.K. hospitals and what lessons can be learned for future developments and implementation strategies within healthcare settings.Methods: We conducted international, multi-disciplinary, round-table discussions with 21 participants from different backgrounds including policy makers, healthcare organisations, academic researchers, vendors and patient representatives. The discussions were audio-recorded, transcribed and then thematically analysed with the qualitative analysis software NVivo10.Results: There was an over-riding concern that realising financial returns from ePrescribing systems was challenging. The underlying reasons included substantial fixed costs of care provision, the difficulties in radically changing the medicines management process and the lack of capacity within NHS hospitals to analyse and exploit the digital data being generated. Any future data strategy should take into account the need to collect and analyse local and national data (i.e. within and across hospitals), setting comparators to measure progress (i.e. baseline measurements) and clear standards guiding data management so that data are comparable across settings.Conclusions: A more coherent national approach to realising financial benefits from ePrescribing systems is needed as implementations progress and the range of tools to collect information will lead to exponential data growth. The move towards more sophisticated closed-loop systems that integrate prescribing, administration and dispensing, as well as increasingly empowered patients accessing their data through portals and portable devices, will accelerate these developments. Meaningful analysis of data will be the key to realise benefits associated with systems

Non-Poisson variations in photomultipliers and implications for luminescence dating

Previous studies have suggested that excess variations from single-photon counting systems used in luminescence dating may result in underestimation of errors and profoundly influence age models. In this study ten different photon counting systems have been investigated to explore this effect with a greater number of photomultiplier types and instrumental architectures. It is shown that radiation induced phosphorescence from F1 feldspar produces a controllable low-level light source whose local variance approximates Poisson expectations. However excess variation in dark counts was observed to varying extents from all systems. The excess variance is slightly anti-correlated with the age of the system, with older devices conforming more closely to Poisson behaviour. This observation does not seem to fit the hypothesis that enhanced levels of helium diffused into older tubes increase non-Poisson components. It was noted that a significant part of the non-Poisson behaviour was associated with multi-event pulse streams within time series. Work was also undertaken to develop mitigation methods for data analysis and to examine the implications for dating uncertainties in a test case. A Poisson-filtering algorithm was developed to identify and remove improbable multi-event streams. Application to data from signal-limited single grains of sediments from a Neolithic chambered tomb in Corsica has shown that, for this case, removing non-Poisson components improves the robustness of retained data, but has less influence on overall dating precision or accuracy. In signal limited applications use of this algorithm to remove one source of excess variation is beneficial. The algorithm and test data are appended to facilitate this.PostprintPeer reviewe

Do UK sheep farmers use orf vaccine correctly and could their vaccination strategy affect vaccine efficacy?

© British Veterinary Association 2019. No commercial re-use. See rights and permissions. Published by BMJ. Orf, a parapoxvirus, is a zoonosis causing a contagious pustular dermatitis, and has a high morbidity in sheep worldwide. Despite a vaccine being available, orf prevalence in England is estimated to be 2 per cent in ewes and 20 per cent in lambsa €a €. There is concern that farmers are not complying with the vaccination guidelines and therefore the objective of this study was to investigate if orf vaccine is used correctly on sheep farms in the UK and to identify barriers and motivators of sheep farmers to use the vaccine. The survey was completed by 570 respondents. The results show several areas of concern; only 27 per cent of respondents used the correct site (axilla), 37 per cent of respondents would use orf vaccine up to a week after opening a vial (shelf life is eight hours), 33 per cent of respondents would vaccinate their ewes too close to lambing and 73 per cent of respondents did not separate vaccinated and non-vaccinated animals (both leading to infection risk for non-vaccinated animals). When vaccinating, only 53 per cent of respondents were wearing gloves and 31 per cent washed their hands just before and immediately after vaccination. Results demonstrate that orf vaccination is not carried out correctly on all UK sheep farms, which is likely to affect vaccine efficacy. A concern around vaccine efficacy, the a € hassle' of the scratch administration, the a € risk of making it worse' and the zoonotic risk when vaccinating were the most common barriers for using orf vaccine, highlighting the importance of veterinary advice when prescribing orf vaccine