Emergency Auxiliary Services: A Bi-Directional Mutual Beneficial Framework for Power Systems and Data Centers
Abstract
The power transmission networks face an increased electrical load at times and locations. This situation gives rise to the problem of demand/supply mismanagement. Therefore, the power systems need fast auxiliary services to keep power management, stability, and reliability in the network. Conventionally, power systems have own dedicated server rooms for executing auxiliary services; however, data centers are among the largest energy consumption clients for the power systems and have the capability to provide enough computational resources to the power system when required. This paper proposes an Emergency Auxiliary Services (EAS) model for power systems and data centers to work combinedly with mutual benefits. A dynamic Service Level Agreement (SLA) is introduced along with an EAS job scheduling algorithm that motivates data center to run power system jobs on priority and effectively during emergency conditions and maintain data center revenue. The EAS includes Optimal Power Flow (OPF) analysis, bus centrality index, and transmission line centrality index. The simulations are performed on real- workload of a data center integrated with IEEE 30-bus system to assess the performance of the proposed model. The results illustrate that the priority execution EAS on data centers has a minimal impact on overall energy consumption and on other cloud computing jobs’ time of execution. Moreover, the dynamic SLA compensates the data center revenue loss due to prior execution of the EAS. Therefore, the SLA encourages the data center operators to execute EAS on priority.
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