Electric vehicle capacity forecasting model with application to load levelling

There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

UV dosimetry for solar water disinfection (SODIS) carried out in different plastic bottles and bags

Solar water disinfection (SODIS) is a well-established inexpensive means of water disinfection in developing countries, but lacks an indicator to illustrate its end-point. A study of the solar UV dosage required for SODIS, in order to achieve a bacteria concentration below the detection limit for: Escherichia coli, Enterococcus spp. and Clostridium perfringens, in water in PET bottles, PE and PE/EVA bags showed disinfection to be most efficient in PE bags, with a solar UV (290–385 nm) dose of 389 kJ m−2 required. In parallel to the disinfection experiments, a range of polyoxometalate, semiconductor photocatalysis and photodegradable dye-based solar UV dosimeter indicators were tested under the same solar UV irradiation conditions. All three types of dosimeter produced indicators that largely and significantly change colour upon exposure to 389 kJ m−2 solar UV; further indicators are reported which change colour at higher doses and hence would be suitable for the less efficient SODIS containers tested. All indicators tested were robust, easy to use and inexpensive so as not to add significantly to the attractive low cost of SODIS. Furthermore, whilst semiconductor photocatalyst and photodegradable dye based indicators are disposable, one-use systems, the polyoxometalate based indicators recover colour in the dark overnight, allowing them to be reused, and hence further decreasing the cost of using indicators during the implementation of the SODIS method.

Residential electrical vehicle charging strategies: the good, the bad and the ugly

In recent years, a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles (EVs). In this paper, we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system. Using this framework and a realistic distribution network simulation testbed, we provide a comparative evaluation of a range of different residential EV charging strategies, highlighting in each case positive and negative characteristics.

A realistic evaluation of Early Warning Systems and acute care training in Northern Ireland: findings and recommendations

Statement of purpose The purpose of this concurrent session is to present the main findings and recommendations from a five year study evaluating the implementation of Early Warning Systems (EWS) and the Acute Life-threatening Events: Recognition and Treatment (ALERT) course in Northern Ireland. The presentation will provide delegates with an understanding of those factors that enable and constrain successful implementation of EWS and ALERT in practice in order to provide an impetus for change. Methods The research design was a multiple case study approach of four wards in two hospitals in Northern Ireland. It followed the principles of realist evaluation research which allowed empirical data to be gathered to test and refine RRS programme theory [1]. The stages included identifying the programme theories underpinning EWS and ALERT, generating hypotheses, gathering empirical evidence and refining the programme theories. This approach used a variety of mixed methods including individual and focus group interviews, observation and documentary analysis of EWS compliance data and ALERT training records. A within and across case comparison facilitated the development of mid-range theories from the research evidence. Results The official RRS theories developed from the realist synthesis were critically evaluated and compared with the study findings to develop a mid-range theory to explain what works, for whom in what circumstances. The findings of what works suggests that clinical experience, established working relationships, flexible implementation of protocols, ongoing experiential learning, empowerment and pre-emptive management are key to the success of EWS and ALERT implementation. Each concept is presented as ‘context, mechanism and outcome configurations’ to provide an understanding of how the context impacts on individual reasoning or behaviour to produce certain outcomes. Conclusion These findings highlight the combination of factors that can improve the implementation and sustainability of EWS and ALERT and in light of this evidence several recommendations are made to provide policymakers with guidance and direction for future policy development. References: 1. Pawson R and Tilley N. (1997) Realistic Evaluation. Sage Publications; London Type of submission: Concurrent session Source of funding: Sandra Ryan Fellowship funded by the School of Nursing & Midwifery, Queen’s University of Belfast

Early warning systems: problems, pragmatics and potential

Symposium Chair: Dr Jennifer McGaughey

Title: Early Warning Systems: problems, pragmatics and potential

Early Warning Systems (EWS) provide a mechanism for staff to recognise, refer and manage deteriorating patients on general hospital wards. Implementation of EWS in practice has required considerable change in the delivery of critical care across hospitals. Drawing their experience of these changes the authors will demonstrate the problems and potential of using EWS to improve patient outcomes.

The first paper (Dr Jennifer McGaughey: Early Warning Systems: what works?) reviews the research evidence regarding the factors that support or constrain the implementation of Early Warning System (EWS) in practice. These findings explain those processes which impact on the successful achievement of patient outcomes. In order to improve detection and standardise practice National EWS have been implemented in the United Kingdom. The second paper (Catherine Plowright: The implementation of the National EWS in a District General Hospital) focuses on the process of implementing and auditing a National EWS. This process improvement is essential to contribute to future collaborative research and collection of robust datasets to improve patient safety as recommended by the Royal College of Physicians (RCP 2012). To successfully implement NEWS in practice requires strategic planning and staff education. The practical issues of training staff is discussed in the third paper. This paper (Collette Laws-Chapman: Simulation as a modality to embed the use of Early Warning Systems) focuses on using simulation and structured debrief to enhance learning in the early recognition and management of deteriorating patients. This session emphasises the importance of cognitive and social skills developed alongside practical skills in the simulated setting.

Experimental validation of a drive-by stiffness identification method for bridge monitoring

An experimental investigation is carried out to verify the feasibility of using an instrumented vehicle to detect and monitor bridge dynamic parameters. The low-cost method consists of the use of a moving vehicle fitted with accelerometers on its axles. In the laboratory experiment, the vehicle–bridge interaction model consists of a scaled two-axle vehicle model crossing a simply supported steel beam. The bridge model also includes a scaled road surface profile. The effects of varying the vehicle model configuration and speed are investigated. A finite element beam model is calibrated using the experimental results, and a novel algorithm for the identification of global bridge stiffness is validated. Using measured vehicle accelerations as input to the algorithm, the beam stiffness is identified with a reasonable degree of accuracy.

Experimental Investigation of the Detection of Bridge Dynamic Parameters using a Moving Vehicle

This paper investigates the feasibility of using an instrumented vehicle to detect bridge dynamic parameters, such as natural frequency and structural damping, in a scaled laboratory experiment. In the experiment, a scaled vehicle model crosses a steel girder which has been adopted as the bridge model. The bridge model also includes a scaled road surface profile. The effects of varying vehicle model mass and speed are investigated. The damping of the girder is also varied. The bridge frequency and changes in damping are detected in the vehicle acceleration response in the presence of a rough road surface profile.

Using Instrumented Vehicles To Detect Damage in Bridges

Bridge structures are subject to continuous degradation due to the environment, ageing and excess loading. Monitoring of bridges is a key part of any maintenance strategy as it can give early warning if a bridge is becoming unsafe. This paper will theoretically assess the ability of a vehicle fitted with accelerometers on its axles to detect changes in damping of bridges, which may be the result of damage. Two vehicle models are used in this investigation. The first is a two degree-of-freedom quarter-car and the second is a four degree-of-freedom halfcar. The bridge is modelled as a simply supported beam and the interaction between the vehicle and the bridge is a coupled dynamic interaction algorithm. Both smooth and rough road profiles are used in the simulation and results indicate that changes in bridge damping can be detected by the vehicle models for a range of vehicle velocities and bridge spans.