Architectures for smart end-user services in the power grid

Abstract-The increase of distributed renewable electricity generators, such as solar cells and wind turbines, requires a new energy management system. These distributed generators introduce bidirectional energy flows in the low-voltage power grid, requiring novel coordination mechanisms to balance local supply and demand. Closed solutions exist for energy management on the level of individual homes. However, no service architectures have been defined that allow the growing number of end-users to interact with the other power consumers and generators and to get involved in more rational energy consumption patterns using intuitive applications. We therefore present a common service architecture that allows houses with renewable energy generation and smart energy devices to plug into a distributed energy management system, integrated with the public power grid. Next to the technical details, we focus on the usability aspects of the end-user applications in order to contribute to high service adoption and optimal user involvement. The presented architecture facilitates end-users to reduce net energy consumption, enables power grid providers to better balance supply and demand, and allows new actors to join with new services. We present a novel simulator that allows to evaluate both the power grid and data communication aspects, and illustrate a 22% reduction of the peak load by deploying a central coordinator inside the home gateway of an end-user

A Parallel Algorithm for solving BSDEs - Application to the pricing and hedging of American options

We present a parallel algorithm for solving backward stochastic differential equations (BSDEs in short) which are very useful theoretic tools to deal with many financial problems ranging from option pricing option to risk management. Our algorithm based on Gobet and Labart (2010) exploits the link between BSDEs and non linear partial differential equations (PDEs in short) and hence enables to solve high dimensional non linear PDEs. In this work, we apply it to the pricing and hedging of American options in high dimensional local volatility models, which remains very computationally demanding. We have tested our algorithm up to dimension 10 on a cluster of 512 CPUs and we obtained linear speedups which proves the scalability of our implementationComment: 25 page

Automating property-based testing of evolving web services

Web services are the most widely used service technology that drives the Service-Oriented Computing~(SOC) paradigm. As a result, effective testing of web services is getting increasingly important. In this paper, we present a framework and toolset for testing web services and for evolving test code in sync with the evolution of web services. Our approach to testing web services is based on the Erlang programming language and QuviQ QuickCheck, a property-based testing tool written in Erlang, and our support for test code evolution is added to Wrangler, the Erlang refactoring tool. The key components of our system include the automatic generation of initial test code, the inference of web service interface changes between versions, the provision of a number of domain specific refactorings and the automatic generation of refactoring scripts for evolving the test code. Our framework provides users with a powerful and expressive web service testing framework, while minimising users' effort in creating, maintaining and evolving the test model. The framework presented in this paper can be used by both web service providers and consumers, and can be used to test web services written in whatever language; the approach advocated here could also be adopted in other property-based testing frameworks and refactoring tools