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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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/159025 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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). |
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