Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/159025
Title: Probabilistic forecasting of residential load power for smart home
Authors: Du, Zhenyuan
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: 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
Abstract: 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).
URI: https://hdl.handle.net/10356/159025
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

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