Optioneering analysis for connecting Dogger Bank offshore wind farms to the GB electricity network

This paper outlines possibilities for connecting 2.4 GW of power from two separate wind farms at Dogger Bank in the North Sea to the GB transmission system in Great Britain. Three options based on HVDC with Voltage Source Converters (VSC HVDC) are investigated: two separate point-to-point connections, a four-terminal multi-terminal network and a four-terminal network with the addition of an AC auxiliary cable between the two wind farms. Each option is investigated in terms of investment cost, controllability and reliability against expected fault scenarios. The paper concludes that a VSC-HVDC point-to-point connection is the cheapest option in terms of capital cost and has the additional advantage that it uses technology that is commercially available. However, while multi-terminal connections are more expensive to build it is found that they can offer significant advantages over point to point systems in terms of security of supply and so could offer better value for money overall. A multi-terminal option with an auxiliary AC connection between wind farms is found to be lower cost than a full multi-terminal DC grid option although the latter network would offer ability to operate at greater connection distances between substations

Gesture based IoT light control for smart clothing

In this paper, a smart wireless wristband is proposed. The potential of innovative gesture based interactivity with connected lighting solutions is reviewed. The solution is intended to offer numerous benefits, in terms of ease of use, and enhanced dynamic interactive functionality. A comparative analysis will be carried out between this work and existing solutions. The evolution of lighting and gesture controls will be discussed and an overview of alternative applications will be provided, as part of the critical analysis

Pervasive eHealth services a security and privacy risk awareness survey

The human factor is often recognised as a major aspect of cyber-security research. Risk and situational perception are identified as key factors in the decision making process, often playing a lead role in the adoption of security mechanisms. However, risk awareness and perception have been poorly investigated in the field of eHealth wearables. Whilst end-users often have limited understanding of privacy and security of wearables, assessing the perceived risks and consequences will help shape the usability of future security mechanisms. This paper present a survey of the the risks and situational awareness in eHealth services. An analysis of the lack of security and privacy measures in connected health devices is described with recommendations to circumvent critical situations

A study on situational awareness security and privacy of wearable health monitoring devices

Situational Awareness provides a user centric approach to security and privacy. The human factor is often recognised as the weakest link in security, therefore situational perception and risk awareness play a leading role in the adoption and implementation of security mechanisms. In this study we assess the understanding of security and privacy of users in possession of wearable devices. The findings demonstrate privacy complacency, as the majority of users trust the application and the wearable device manufacturer. Moreover the survey findings demonstrate a lack of understanding of security and privacy by the sample population. Finally the theoretical implications of the findings are discussed

A decision support framework for proactive maintenance of water and wastewater systems

Proactive maintenance of assets is a much sought after goal in the water and wastewater industry, where substantial savings could be made by identifying impending failures in pumps and other essential components of the system. A detailed analysis of the operational behaviour of the monitored assets can be used as the foundation to generate estimations on the likelihood of a failure or malfunction in a particular component based on knowledge of previous behavioural patterns. Preventative maintenance or component replacement can then be optimally scheduled based on need, as opposed to traditional reactive maintenance strategies. In most current condition monitoring software, an alarm is normally raised once a fault has occurred, therefore often requiring immediate action. On the other hand, combining the condition monitoring and fault log data that is normally acquired with expert knowledge of the meaning and causes of faults embedded in the software allows predictive maintenance to be implemented. The paper reports on a number of advanced machine learning techniques that have been applied to operational data acquired over a significant period of water pump operation. Results from a representative site within Scottish Water's water network will be presented that demonstrate the application of such software techniques can indeed surface changes in parameters, for example flow and pump power drawn, forming the basis to infer the state of components and the onset of changes in the health of the asset

North Sea offshore modelling schemes with VSC-HVDC technology : control and dynamic performance assessment

The present thinking and trend for connection of large offshore wind farms, dispersed over wide areas, is to use multi-terminal HVDC networks rather than point-to-point DC transmission systems. The aim behind this approach is to improve the security of supply and minimise the loss of generation during scheduled maintenance or unexpected disturbances in any part of the power network. This paper describes various models of multi-terminal HVDC networks connecting offshore wind farms to a number of mainland AC grids which have been developed in MATLAB-Simulink with the main objective of facilitating numerous studies such as steady-state power flow, optimal power dispatch analysis, transient stability, and provision of ancillaries