Identifying Useful Statistical Indicators of Proximity to Instability in Stochastic Power Systems

@article{Ghanavati2016IdentifyingUS,
  title={Identifying Useful Statistical Indicators of Proximity to Instability in Stochastic Power Systems},
  author={Goodarz Ghanavati and Paul D. H. Hines and Taras I. Lakoba},
  journal={IEEE Transactions on Power Systems},
  year={2016},
  volume={31},
  pages={1360-1368}
}
Prior research has shown that autocorrelation and variance in voltage measurements tend to increase as power systems approach instability. This paper seeks to identify the conditions under which these statistical indicators provide reliable early warning of instability in power systems. First, the paper derives and validates a semi-analytical method for quickly calculating the expected variance and autocorrelation of all voltages and currents in an arbitrary power system model. Building on this… CONTINUE READING
Highly Cited
This paper has 18 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 15 extracted citations

Data-Driven Diagnostics of Mechanism and Source of Sustained Oscillations

IEEE Transactions on Power Systems • 2016
View 4 Excerpts
Highly Influenced

Online Learning of Power Transmission Dynamics

2018 Power Systems Computation Conference (PSCC) • 2018
View 2 Excerpts

Complex Networks Theory For Modern Smart Grid Applications: A Survey

IEEE Journal on Emerging and Selected Topics in Circuits and Systems • 2017

Estimating dynamic load parameters from ambient PMU measurements

2017 IEEE Power & Energy Society General Meeting • 2017
View 1 Excerpt

References

Publications referenced by this paper.
Showing 1-10 of 48 references

Critical slowing-down as indicator of approach to the loss of stability

2014 IEEE International Conference on Smart Grid Communications (SmartGridComm) • 2014

Model-free voltage stability assessments via singular value analysis of PMU data

2013 IREP Symposium Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid • 2013

Similar Papers

Loading similar papers…