Probabilistic forecasting of residential load power for smart home
Due to the stochastic nature of occupants’ behaviors, forecasting individual household-level residential load for smart home has been a challenging problem. This paper proposes a probabilistic residential load power forecasting method for smart home considering three aspects: deep-learning-based poi...
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/159025 |
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sg-ntu-dr.10356-1590252022-06-05T12:04:43Z Probabilistic forecasting of residential load power for smart home Du, Zhenyuan Xu Yan School of Electrical and Electronic Engineering xuyan@ntu.edu.sg Engineering::Electrical and electronic engineering Due to the stochastic nature of occupants’ behaviors, forecasting individual household-level residential load for smart home has been a challenging problem. This paper proposes a probabilistic residential load power forecasting method for smart home considering three aspects: deep-learning-based point-forecasting of residential load, prediction intervals to estimate the load uncertainties, and non-intrusive load monitoring (NILM). Master of Science (Computer Control and Automation) 2022-06-05T12:04:42Z 2022-06-05T12:04:42Z 2022 Thesis-Master by Coursework Du, Z. (2022). Probabilistic forecasting of residential load power for smart home. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/159025 https://hdl.handle.net/10356/159025 en application/pdf Nanyang Technological University |
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NTU Library |
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Singapore Singapore |
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Engineering::Electrical and electronic engineering |
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Engineering::Electrical and electronic engineering Du, Zhenyuan Probabilistic forecasting of residential load power for smart home |
| description |
Due to the stochastic nature of occupants’ behaviors, forecasting individual household-level residential load for smart home has been a challenging problem. This paper proposes a probabilistic residential load power forecasting method for smart home considering three aspects: deep-learning-based point-forecasting of residential load, prediction intervals to estimate the load uncertainties, and non-intrusive load monitoring (NILM). |
| author2 |
Xu Yan |
| author_facet |
Xu Yan Du, Zhenyuan |
| format |
Thesis-Master by Coursework |
| author |
Du, Zhenyuan |
| author_sort |
Du, Zhenyuan |
| title |
Probabilistic forecasting of residential load power for smart home |
| title_short |
Probabilistic forecasting of residential load power for smart home |
| title_full |
Probabilistic forecasting of residential load power for smart home |
| title_fullStr |
Probabilistic forecasting of residential load power for smart home |
| title_full_unstemmed |
Probabilistic forecasting of residential load power for smart home |
| title_sort |
probabilistic forecasting of residential load power for smart home |
| publisher |
Nanyang Technological University |
| publishDate |
2022 |
| url |
https://hdl.handle.net/10356/159025 |
| _version_ |
1735491110882508800 |