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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2018
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th-cmuir.6653943832-535222018-09-04T09:50:48Z Electricity load classification using K-means clustering algorithm Somboon Nuchprayoon Engineering 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. 2018-09-04T09:50:48Z 2018-09-04T09:50:48Z 2014-01-01 Conference Proceeding 2-s2.0-84949986766 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84949986766&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/53522 |
| institution |
Chiang Mai University |
| building |
Chiang Mai University Library |
| country |
Thailand |
| collection |
CMU Intellectual Repository |
| topic |
Engineering |
| spellingShingle |
Engineering Somboon Nuchprayoon Electricity load classification using K-means clustering algorithm |
| description |
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. |
| format |
Conference Proceeding |
| author |
Somboon Nuchprayoon |
| author_facet |
Somboon Nuchprayoon |
| author_sort |
Somboon Nuchprayoon |
| title |
Electricity load classification using K-means clustering algorithm |
| title_short |
Electricity load classification using K-means clustering algorithm |
| title_full |
Electricity load classification using K-means clustering algorithm |
| title_fullStr |
Electricity load classification using K-means clustering algorithm |
| title_full_unstemmed |
Electricity load classification using K-means clustering algorithm |
| title_sort |
electricity load classification using k-means clustering algorithm |
| publishDate |
2018 |
| url |
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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