Towards a Cloud Infrastructure for Energy Informatics
| Zhengkai Wu Georgia Institute of Technology, USA |
| Michael E. Cotterell University of Georgia, USA |
| Sun Qin Georgia Institute of Technology, USA |
| Aaron Beach National Renewable Energy Laboratory, USA |
| Grijalva Santiago Georgia Institute of Technology, USA |
Abstract
The development of cloud computing has achieved the goal of computing as a service, abstracting the resource "as a cloud". This service has extended to include not only computation but its associated storage and communication components as well. The smart grid hopes to integrate the dynamics of distributed generation and demand. If the computational requirements of these demands are as dynamic as the phenomena they seek to control, then the cloud computing model provides an appropriately flexible platform for smart grid computing. This paper evaluates the Cloud for Energy Informatics (CEI), a computational-control abstraction that provides flexible and efficient computational resources on-demand as defined by the smart grid. We focus on how the CEI addresses performance and efficiency measures of smart grid related computation such as latency, bandwidth, storage and compute cycles. We compare CEI with traditional approaches using simulation to quantify the resource savings, efficiency and reliability gains from switching to a CEI model.
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| Reference: | Wu, Z., Cotterell, M., Qin, S., Beach, A., Santiago, G. (2012). "Towards a Cloud Infrastructure for Energy Informatics," Proceedings > Proceedings of Energy Informatics . Sprouts: Working Papers on Information Systems, 12(7). http://sprouts.aisnet.org/12-7 | |||
| Keywords: | Cloud for Energy Informatics, Service-Oriented Network, Energy Efficiency Metrics, Classified-Power Capping, Optimal Energy Saving | |||
| Item Type: | Article - Volume 12 Article 7 (2012) | |||
| Language: | English | |||
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