Journal article

Robust Recovery of Missing Data in Electricity Distribution Systems

Cristian Genes, Inaki Esnaola, Samir M Perlaza, Luis F Ochoa, Daniel Coca

IEEE Transactions on Smart Grid | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2019

Abstract

The advanced operation of future electricity distribution systems is likely to require significant observability of the different parameters of interest (e.g., demand, voltages, currents, etc.). Ensuring completeness of data is, therefore, paramount. In this context, an algorithm for recovering missing state variable observations in electricity distribution systems is presented. The proposed method exploits the low rank structure of the state variables via a matrix completion approach incorporating prior knowledge in the form of second order statistics. Essentially, the recovery method combines nuclear norm minimization with Bayesian estimation. The performance of the new algorithm is compar..

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Grants

Awarded by EPSRC UKCRIC


Funding Acknowledgements

This work was supported in part by the University of Sheffield Future Cities Scholarship and EPSRC UKCRIC under Grant EP/R013411/1, Grant EP/R012202/1, and Grant EP/P016782/1, and in part by the Euro-Mediterranean Cooperation ERA-NET Project COM-MED.