‘Smart Cities’ – Dynamic Sustainability Issues and Challenges for ‘Old World’ Economies: A Case from the United Kingdom

The rapid and dynamic rate of urbanization, particularly in emerging world economies, has resulted in a need to find sustainable ways of dealing with the excessive strains and pressures that come to bear on existing infrastructures and relationships. Increasingly during the twenty-first century policy makers have turned to technological solutions to deal with this challenge and the dynamics inherent within it. This move towards the utilization of technology to underpin infrastructure has led to the emergence of the term ‘Smart City’. Smart cities incorporate technology based solutions in their planning development and operation. This paper explores the organizational issues and challenges facing a post-industrial agglomeration in the North West of England as it attempted to become a ‘Smart City’. In particular the paper identifies and discusses the factors that posed significant challenges for the dynamic relationships residents, policymakers and public and private sector organizations and as a result aims to use these micro-level issues to inform the macro-debate and context of wider Smart City discussions. In order to achieve this, the paper develops a range of recommendations that are designed to inform Smart City design, planning and implementation strategies

Smart grid interoperability use cases for extending electricity storage modeling within the IEC Common Information Model

Copyright @ 2012 IEEEThe IEC Common Information Model (CIM) is recognized as a core standard, supporting electricity transmission system interoperability. Packages of UML classes make up its domain ontology to enable a standardised abstraction of network topology and proprietary power system models. Since the early days of its design, the CIM has grown to reflect the widening scope and detail of utility information use cases as the desire to interoperate between a greater number of systems has increased. The cyber-physical nature of the smart grid places even greater demand upon the CIM to model future scenarios for power system operation and management that are starting to arise. Recent developments of modern electricity networks have begun to implement electricity storage (ES) technologies to provide ancillary balancing services, useful to grid integration of large-scale renewable energy systems. In response to this we investigate modeling of grid-scale electricity storage, by drawing on information use cases for future smart grid operational scenarios at National Grid, the GB Transmission System Operator. We find current structures within the CIM do not accommodate the informational requirements associated with novel ES systems and propose extensions to address this requirement.This study is supported by the UK National Grid and Brunel Universit

End-to-End Navigation in Unknown Environments using Neural Networks

We investigate how a neural network can learn perception actions loops for navigation in unknown environments. Specifically, we consider how to learn to navigate in environments populated with cul-de-sacs that represent convex local minima that the robot could fall into instead of finding a set of feasible actions that take it to the goal. Traditional methods rely on maintaining a global map to solve the problem of over coming a long cul-de-sac. However, due to errors induced from local and global drift, it is highly challenging to maintain such a map for long periods of time. One way to mitigate this problem is by using learning techniques that do not rely on hand engineered map representations and instead output appropriate control policies directly from their sensory input. We first demonstrate that such a problem cannot be solved directly by deep reinforcement learning due to the sparse reward structure of the environment. Further, we demonstrate that deep supervised learning also cannot be used directly to solve this problem. We then investigate network models that offer a combination of reinforcement learning and supervised learning and highlight the significance of adding fully differentiable memory units to such networks. We evaluate our networks on their ability to generalize to new environments and show that adding memory to such networks offers huge jumps in performanceComment: Workshop on Learning Perception and Control for Autonomous Flight: Safety, Memory and Efficiency, Robotics Science and Systems 201

A bounded upwinding scheme for computing convection-dominated transport problems

A practical high resolution upwind differencing scheme for the numerical solution of convection-dominated transport problems is presented. The scheme is based on TVD and CBC stability criteria and is implemented in the context of the finite difference methodology. The performance of the scheme is investigated by solving the 1D/2D scalar advection equations, 1D inviscid Burgers’ equation, 1D scalar convection–diffusion equation, 1D/2D compressible Euler’s equations, and 2D incompressible Navier–Stokes equations. The numerical results displayed good agreement with other existing numerical and experimental data

Priorities, policies and (time)scales : the delivery of emissions reductions in the UK transport sector

Peer reviewedPreprin

Spontaneous emergence of spatial patterns ina a predator-prey model

We present studies for an individual based model of three interacting populations whose individuals are mobile in a 2D-lattice. We focus on the pattern formation in the spatial distributions of the populations. Also relevant is the relationship between pattern formation and features of the populations' time series. Our model displays travelling waves solutions, clustering and uniform distributions, all related to the parameters values. We also observed that the regeneration rate, the parameter associated to the primary level of trophic chain, the plants, regulated the presence of predators, as well as the type of spatial configuration.Comment: 17 pages and 15 figure