Electricity load classification using K-means clustering algorithm
K-means clustering method is applied to classify electricity load data into five groups. The load groups are super-peak, peak, cycling, intermediate, and base. On the other hand, when only three groups are needed, the peak load is combined with the cycling load and the intermediate load is combined...
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| Main Author: | |
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| Format: | Conference Proceeding |
| Published: |
2018
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| Subjects: | |
| Online Access: | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84949986766&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53522 |
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| Institution: | Chiang Mai University |
| Summary: | K-means clustering method is applied to classify electricity load data into five groups. The load groups are super-peak, peak, cycling, intermediate, and base. On the other hand, when only three groups are needed, the peak load is combined with the cycling load and the intermediate load is combined with the base load. The classification is performed both on annual basis and seasonal basis and shown by using load duration curves. The attributes of load group are load level and duration. The proposed method has been implemented by using statistical analysis software SPSS and tested with the hourly generation data of Thailand during 2009-2011. |
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