Biblio

Modern day grid operation requires multiple interlinked applications and many automated processes at control center for monitoring and operation of grid. Information technology integrated with operational technology plays a critical role in grid operation. Computing resource requirements of these software applications varies widely and includes high processing applications, high Input/Output (I/O) sensitive applications and applications with low resource requirements. Present day grid operation control center uses various applications for load despatch schedule management, various real-time analytics & optimization applications, post despatch analysis and reporting applications etc. These applications are integrated with Operational Technology (OT) like Data acquisition system / Energy management system (SCADA/EMS), Wide Area Measurement System (WAMS) etc. This paper discusses various design considerations and implementation of converged infrastructure through virtualization technology by consolidation of servers and storages using multi-cluster approach to meet high availability requirement of the applications and achieve desired objectives of grid control center of north eastern region in India. The process involves weighing benefits of different architecture solution, grouping of application hosts, making multiple clusters with reliability and security considerations, and designing suitable infrastructure to meet all end objectives. Reliability, enhanced resource utilization, economic factors, storage and physical node selection, integration issues with OT systems and optimization of cost are the prime design considerations. Modalities adopted to minimize downtime of critical systems for grid operation during migration from the existing infrastructure and integration with OT systems of North Eastern Regional Load Despatch Center are also elaborated in this paper.

There are multiple steps involved in transitioning a server from the factory to being fully provisioned for an intended workload. These steps include finding the optimal slot for the hardware and to compose the required resources on the hardware for the intended workload. There are many different factors that influence the placement of server hardware in the datacenter, such as physical limitations to connect to a network be it Ethernet or storage networks, power requirements, temperature/cooling considerations, and physical space, etc. In addition to this, there may be custom requirements driven by workload policies (such as security, data privacy, power redundancy, etc.). Once the server has been placed in the right slot it needs to be configured with the appropriate resources for the intended workload. CIED will provide a ranked list of locations for server placement based on the intended workload, connectivity and physical requirements of the server. Once the server is placed in the suggested slot, the solution automatically discovers the server and composes the required resources (compute, storage and networks) for running the appropriate workload. CIED reduces the overall time taken to move hardware from factory to production and also maximizes the server hardware utilization while minimizing downtime by physically placing the resources optimally. From the case study that was undertaken, the time taken to transition a server from factory to being fully provisioned was proportional to the number of devices in the datacenter. With CIED this time is constant irrespective of the complexity or the number of devices in a datacenter.