Predicting Hourly Residential Energy Consumption using Random Forest and Support Vector Regression : An Analysis of the Impact of Household Clustering on the Performance Accuracy
The recent increase of smart meters in the residential sector has lead to large available datasets. The electricity consumption of individual households can be accessed in close to real time, and allows both the demand and supply side to extract valuable information for efficient energy management....
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| Format: | Others |
| Language: | English |
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KTH, Matematisk statistik
2016
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187873 |