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 | Schools: | School of Electrical and Electronic Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
[DU ZHENYUAN(G2103702E)].pdf Restricted Access | 1.94 MB | Adobe PDF | View/Open |
Page view(s)
158
Updated on Mar 28, 2024
Download(s)
9
Updated on Mar 28, 2024
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.