Data-Driven Preemptive Voltage Monitoring and Control Using Probabilistic Voltage Sensitivities

Venkat Krishnan, Yingchen Zhang, Kumarsinh Jhala, Balasubramaniam Natarajan

Research output: Contribution to conferencePaper

11 Scopus Citations

Abstract

Increased penetration levels of distributed variable renewable generation can cause random voltage fluctuations and violations at multiple nodes. Traditional methods of voltage control typically involve reactionary responses of capacitor banks, tap changers, and recently even smart inverters. But because of the lack of foresight in voltage violations, these controls are ineffective to completely mitigate the issue. Therefore, new methods of predicting voltage violations subject to random power injection changes in the distribution network are needed, which can be used to guide optimal and dynamic methods of voltage control. This work lays the foundation for such preemptive voltage monitoring and control by proposing an analytical and sensor data-driven voltage sensitivity analysis method. Driven by stochastic data and forecasts, the method can be used to develop probabilistic voltage sensitivities and consequently to predict system nodes with high likelihood of voltage limit violations. The effectiveness of this method is tested on IEEE 69-node distribution system integrated with distributed solar. The results demonstrate the proposed method's ability to successfully predict nodes with high probability of voltage violations for a specific time-series simulation. The results also demonstrate the ability to guide timely power injection control actions to mitigate future voltage violations.
Original languageAmerican English
Number of pages5
DOIs
StatePublished - 2020
Event2019 IEEE Power & Energy Society General Meeting (PESGM) - Atlanta, Georgia
Duration: 4 Aug 20198 Aug 2019

Conference

Conference2019 IEEE Power & Energy Society General Meeting (PESGM)
CityAtlanta, Georgia
Period4/08/198/08/19

Bibliographical note

See NREL/CP-5D00-72661 for preprint

NREL Publication Number

  • NREL/CP-5D00-76225

Keywords

  • control
  • distributed generation
  • distribution systems
  • monitoring
  • preemptive
  • probability
  • sensitivity
  • sensor measurement
  • voltage

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