Architecture for Data Coordination Processing and Real Time Services in Smart Grid Environment


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Abstract


Smart grid is a complex network, consisting of large number of energy sources, controlling devices and load centers. The time varying characteristics of these grid elements demands a dynamic smart grid management platform for offering various services. The cloud environment provides a flexible way of building and facilitating computing and storage infrastructures for various online and offline services. In this paper, an architecture is presented for coordination and processing of linked data in smart grid environment. Priority strategy is considered for application level performance management in the framework. The architecture offers data storage and management with minimum hardware. Also it supports different spatial and temporal requirements for operation services.
The case is simulated to evaluate the suitability of cloud architecture for real time services. The simulation experiment has been conducted in the Cloud test bed. Analytical model based on queuing theory has been developed for performance evaluation. The test results show that, the architecture can effectively handle the data coordination and processing in smart grid environment to offer various online services. The priority strategy provides significant improvement in the performance result.


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Keywords


Mean Response Time; Openstack; Smart Grid; Scheduler; Virtual Machine

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