Scenarios for the development of smart grids in the UK: synthesis report

‘Smart grid’ is a catch-all term for the smart options that could transform the ways society produces, delivers and consumes energy, and potentially the way we conceive of these services. Delivering energy more intelligently will be fundamental to decarbonising the UK electricity system at least possible cost, while maintaining security and reliability of supply. Smarter energy delivery is expected to allow the integration of more low carbon technologies and to be much more cost effective than traditional methods, as well as contributing to economic growth by opening up new business and innovation opportunities. Innovating new options for energy system management could lead to cost savings of up to £10bn, even if low carbon technologies do not emerge. This saving will be much higher if UK renewable energy targets are achieved. Building on extensive expert feedback and input, this report describes four smart grid scenarios which consider how the UK’s electricity system might develop to 2050. The scenarios outline how political decisions, as well as those made in regulation, finance, technology, consumer and social behaviour, market design or response, might affect the decisions of other actors and limit or allow the availability of future options. The project aims to explore the degree of uncertainty around the current direction of the electricity system and the complex interactions of a whole host of factors that may lead to any one of a wide range of outcomes. Our addition to this discussion will help decision makers to understand the implications of possible actions and better plan for the future, whilst recognising that it may take any one of a number of forms

GPU-accelerated discontinuous Galerkin methods on hybrid meshes

We present a time-explicit discontinuous Galerkin (DG) solver for the time-domain acoustic wave equation on hybrid meshes containing vertex-mapped hexahedral, wedge, pyramidal and tetrahedral elements. Discretely energy-stable formulations are presented for both Gauss-Legendre and Gauss-Legendre-Lobatto (Spectral Element) nodal bases for the hexahedron. Stable timestep restrictions for hybrid meshes are derived by bounding the spectral radius of the DG operator using order-dependent constants in trace and Markov inequalities. Computational efficiency is achieved under a combination of element-specific kernels (including new quadrature-free operators for the pyramid), multi-rate timestepping, and acceleration using Graphics Processing Units.Comment: Submitted to CMAM

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

EOR as sequestration: Geoscience perspective

CO2 Enhanced Oil Recovery (EOR) has a development and operational history several decades longer than geologic sequestration of CO2 designed to benefit the atmosphere and provides much of the experience on which confidence in the newer technology is based. With modest increases in surveillance and accounting, future CO2 EOR using anthropogenic CO2 (CO2-A) captured to decrease atmospheric emissions can be used as part of a sequestration program.Bureau of Economic Geolog

TCG based approach for secure management of virtualized platforms: state-of-the-art

There is a strong trend shift in the favor of adopting virtualization to get business benefits. The provisioning of virtualized enterprise resources is one kind of many possible scenarios. Where virtualization promises clear advantages it also poses new security challenges which need to be addressed to gain stakeholders confidence in the dynamics of new environment. One important facet of these challenges is establishing 'Trust' which is a basic primitive for any viable business model. The Trusted computing group (TCG) offers technologies and mechanisms required to establish this trust in the target platforms. Moreover, TCG technologies enable protecting of sensitive data in rest and transit. This report explores the applicability of relevant TCG concepts to virtualize enterprise resources securely for provisioning, establish trust in the target platforms and securely manage these virtualized Trusted Platforms

86 PFLOPS Deep Potential Molecular Dynamics simulation of 100 million atoms with ab initio accuracy

We present the GPU version of DeePMD-kit, which, upon training a deep neural network model using ab initio data, can drive extremely large-scale molecular dynamics (MD) simulation with ab initio accuracy. Our tests show that the GPU version is 7 times faster than the CPU version with the same power consumption. The code can scale up to the entire Summit supercomputer. For a copper system of 113, 246, 208 atoms, the code can perform one nanosecond MD simulation per day, reaching a peak performance of 86 PFLOPS (43% of the peak). Such unprecedented ability to perform MD simulation with ab initio accuracy opens up the possibility of studying many important issues in materials and molecules, such as heterogeneous catalysis, electrochemical cells, irradiation damage, crack propagation, and biochemical reactions.Comment: 29 pages, 11 figure

Modeling Profit of Sliced 5G Networks for Advanced Network Resource Management and Slice Implementation

The core innovation in future 5G cellular networksnetwork slicing, aims at providing a flexible and efficient framework of network organization and resource management. The revolutionary network architecture based on slices, makes most of the current network cost models obsolete, as they estimate the expenditures in a static manner. In this paper, a novel methodology is proposed, in which a value chain in sliced networks is presented. Based on the proposed value chain, the profits generated by different slices are analyzed, and the task of network resource management is modeled as a multiobjective optimization problem. Setting strong assumptions, this optimization problem is analyzed starting from a simple ideal scenario. By removing the assumptions step-by-step, realistic but complex use cases are approached. Through this progressive analysis, technical challenges in slice implementation and network optimization are investigated under different scenarios. For each challenge, some potentially available solutions are suggested, and likely applications are also discussed