Missing data treatment of the load profiles in distribution networks

In distribution systems, the determination of the load is relatively simple when measurements are available. Frequently, due to various causes such as metering and transmission equipment failures, data are missing for part or all of a day. In these cases, estimation a ldquocorrectedrdquo value must...

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Bibliographic Details
Main Authors: Grigoras, G., Cartina, G., Bobric, E.C., Barbulescu, C.
Format: Conference Proceeding
Language:English
Subjects:
clustering method
Clustering methods
Data analysis
distribution networks
Equipment failure
Failure analysis
fuzzy kNNs method
Information retrieval
Load modeling
load profile
missing data
Monitoring
State estimation
Telemetry
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Summary:In distribution systems, the determination of the load is relatively simple when measurements are available. Frequently, due to various causes such as metering and transmission equipment failures, data are missing for part or all of a day. In these cases, estimation a ldquocorrectedrdquo value must be made. The paper presents two methods (k-Nearest Neighbors, (kNNs) and Clustering methods) for treatment of missing data problems in electric distribution networks. The numerical results indicate that the methods are efficient in the estimation of the missing load values for electric distribution stations.
DOI:10.1109/PTC.2009.5282021