4 Scopus citations

Abstract

Being one of the key derivatives of phasor measurement units (PMUs), a synchrophasor-only linear state estimator (LSE) presents a reliable, high quality, and truly dynamic picture of the power grid. However, with the increase in number of buses monitored by PMUs, computational burden will become a critical constraint for the state estimation solver. Although installing additional hardware can be a possible solution, such a solution will considerably raise the cost of capital investment, operation, and maintenance. This paper proposes cloud-computing as a cost-effective alternative to the computational burden problem. This paper also presents feasibility of the cloud based solution with regards to scalability of the system and latency incurred. Our solution is designed to address the critical operational parameters such as latency and variable network sizes. Additionally, the LSE application establishes robust communication procedures to process inputs arriving at high data rates from multiple PMUs. The paper concludes by highlighting future research directions for enhancing such cloud based solutions.

Original languageEnglish (US)
Title of host publication2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538628904
DOIs
StatePublished - Oct 26 2017
Event2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017 - Washington, United States
Duration: Apr 23 2017Apr 26 2017

Publication series

Name2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017

Other

Other2017 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2017
Country/TerritoryUnited States
CityWashington
Period4/23/174/26/17

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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