Smart energy grids enable efficient bidirectional energy supply while reducing cost and GHG emissions. The target smart energy grid will feature distributed energy generation and smart components, which will allow scalable architecture as integrated with interconnected micro grids. In order to facilitate the design and implementation of such dynamic superstructures with local and global performance optimisation, it is important to provide intelligent modelling and simulation environment with distributed decision making capabilities to manage data gathering and analysis functions and map to static and dynamic models of smart energy grid components. This will support the design, control, and operation of smart energy grid in distributed manner, along with the integrated applications. As smart energy grid is a multi-player domain, this requires collaborative decision making and control with distributed knowledgebase to support different views (e.g., utilities, OEM-HEV, and consumers). This will support the automatic and dynamic identification and evaluation of control and protection boundaries and operational scenarios of micro grids with renewable distributed energy generation nodes. In addition, it supports the design and operation of smart energy grid technological architectures as integrated within practical business models related to practical implementation of different components within the smart energy grid architecture. The proposed intelligent and distributed modelling and simulation environment will provide functionalities to support these views. The proposed solution will enable the University of World Institute of Technology to be the leader in smart energy grid with proven low carbon and improved efficiency and reliability of the target smart energy grid infrastructure.
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