IEEE Power & Energy Magazine - May/June 2018 - 63

may/june 2018

ieee power & energy magazine

63

figure 7. A framework for power equipment data cleaning.

Temperature
Air Pressure
Altitude

External Data

Current/Voltage
Active Power
Reactive Power

Power Grid Data

Power Generation Condition
Storage Condition
Transformation Condition

State Monitoring Data

Nameplate Parameters
Fault Records
Maintenance Records

Equipment Data

Input Data

Data Acquisition

Cross-Platform

Data Storage

0
0

100

200

300

400

500

600

100
Noise Data

50

150

Data Before Cleaning
Data After Cleaning

200

300
Missing Data

250

Neural Networks/SVM
Multiple Linear Regression
Extreme Learning Machine
Influencing Factors

Mean Method
Regression Method
Multiple Imputation
K-Nearest Distance Method

Data Cleaning

Abnormal Data Detection
and Governance

Missing Data Imputation

Output Data



Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - May/June 2018

Contents
IEEE Power & Energy Magazine - May/June 2018 - Cover1
IEEE Power & Energy Magazine - May/June 2018 - Cover2
IEEE Power & Energy Magazine - May/June 2018 - Contents
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IEEE Power & Energy Magazine - May/June 2018 - Cover3
IEEE Power & Energy Magazine - May/June 2018 - Cover4
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