Advanced laboratory testing of smart grid applications with power hardware-in-the-loop approach

Power system innovation promoted by the smart grid vision provides large opportunities for the development of a sustainable energy supply infrastructure. However, the increase in system complexity arises the need for innovative planning and operation paradigms to guarantee the optimal and secure grid management. Nonetheless, suitable testing approaches are also required to ensure reliability, safety and proper system integration of innovative smart grid solutions and technologies before deployment. In this work practical issues in the design and operation of advanced smart grid test infrastructures are addressed. Both aspects are analyzed with particular emphasis on test facilities including power hardware-in-the-loop (PHIL) systems. The minimal requirements along with an architectural classification of the elemental laboratory equipment are suggested for the suitable facility design and effective operation. A set of fundamental operational use-cases are formulated for the practical and straightforward applicability of advanced testing approaches especially based on PHIL technique. The assessed design and operational aspects are evaluated on an existing smart grid laboratory equipped with a PHIL system together with typical full-scale smart grid components. Particularly, a number of test-cases are performed to evaluate the major operational aspects with an existing PHIL system. Results show the potential and the actual implementation issues when performing PHIL tests in case of practical applications

Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches

System Engineering and Evolution Decision Support Interim Progress Report (01/01/2000-09/30/2000)

The objective of our effort is to develop a scientific basis for system engineering automation and decision support. This objective addresses the long term goals of increasing the quality of service provided complex systems while reducing development risks, costs, and time. Our work focused on decision support for designing operations of complex modular systems that can include embedded software. Emphasis areas included engineering automation capabilities in the areas of design modifications, design records, reuse, and automatic generation of design representations such as real-time schedules and software