2 research outputs found
Exploiting Semantic Technologies in Smart Environments and Grids: Emerging Roles and Case Studies
Semantic technologies are currently spreading across several application domains as a reliable and consistent mean to address challenges related to organization, manipulation, visualization and exchange of data and knowledge. Different roles are actually played by these techniques depending on the application domain, on the timing constraints, on the distributed nature of applications, and so on. This paper provides an overview of the roles played by semantic technologies in the domain of smart grids and smart environments, with a particular focus on changes brought by such technologies in the adopted architectures, programming techniques and tools. Motivations driving the adoption of semantics in these different, but strictly intertwined, fields are introduced using a strong application-driven perspective. Two real-world case studies in smart grids and smart environments are presented to exemplify the roles covered by such technologies and the changes they fostered in software engineering processes. Learned lessons are then distilled and future adoption scenarios discussed
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Novel processes for smart grid information exchange and knowledge representation using the IEC common information model
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The IEC Common Information Model (CIM) is of central importance in enabling smart grid interoperability. Its continual development aims to meet the needs of the smart grid for semantic understanding and knowledge
representation for a widening domain of resources and processes. With smart grid evolution the importance of information and data management has become an increasingly pressing issue not only because far more data is being generated using modern sensing, control and measuring devices but
also because information is now becoming recognised as the ‘integral component’ that facilitates the optimal flexibility required of the smart grid. This thesis looks at the impacts of CIM implementation upon the landscape of smart grid issues and presents research from within National Grid
contributing to three key areas in support of further CIM deployment. Taking the issue of Enterprise Information Management first, an information management framework is presented for CIM deployment at National Grid. Following this the development and demonstration of a novel secure cloud
computing platform to handle such information is described. Power system application (PSA) models of the grid are partial knowledge representations of a shared reality. To develop the completeness of our understanding of this reality it is necessary to combine these representations.
The second research contribution reports on a novel methodology for a CIM-based
model repository to align PSA representations and provide a
knowledge resource for building utility business intelligence of the grid.
The third contribution addresses the need for greater integration of information relating to energy storage, an essential aspect of smart energy management. It presents the strategic rationale for integrated energy modeling and a novel extension to the existing CIM standards for modeling grid-scale energy storage. Significantly, this work has already contributed to a larger body of work on modeling Distributed Energy Resources currently under development at the Electric Power Research Institute (EPRI) in the
USA.Dr. Martin Bradley on behalf of National Grid Plc. and the Engineering and Physical
Sciences Research Council (EPSRC