Spatiotemporal load curve data cleansing and imputation via sparsity and low rank

Gonzalo Mateos, Georgios B Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The smart grid vision is to build an intelligent power network with an unprecedented level of situational awareness and controllability over its services and infrastructure. This paper advocates statistical inference methods to robustify power monitoring tasks against the outlier effects owing to faulty readings and malicious attacks, as well as against missing data due to privacy concerns and communication errors. In this context, a novel load cleansing and imputation scheme is developed leveraging the low intrinsic-dimensionality of spatiotemporal load profiles and the sparse nature of 'bad data.' A robust estimator based on principal components pursuit (PCP) is adopted, which effects a twofold sparsity-promoting regularization through an ℓ1-norm of the outliers, and the nuclear norm of the nominal load profiles. After recasting the non-separable nuclear norm into a form amenable to distributed optimization, a distributed (D-) PCP algorithm is developed to carry out the imputation and cleansing tasks using a network of interconnected smart meters. Computer simulations and tests with real load curve data corroborate the convergence and effectiveness of the novel D-PCP algorithm.

Original languageEnglish (US)
Title of host publication2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012
Pages653-656
Number of pages4
DOIs
StatePublished - Dec 1 2012
Event2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012 - Tainan, Taiwan, Province of China
Duration: Nov 5 2012Nov 8 2012

Publication series

Name2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012

Other

Other2012 IEEE 3rd International Conference on Smart Grid Communications, SmartGridComm 2012
CountryTaiwan, Province of China
CityTainan
Period11/5/1211/8/12

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