A data-driven bottom-up approach for spatial and temporal electric load forecasting
With the rapid urbanization, electrical infrastructure spreads to raw areas without existing loads. How to achieve accurate long-term load forecasts based on land use plans is a realistic problem. On the other hand, load forecasting (LF) should be extended to high spatial resolutions to guide middle...
Saved in:
Main Authors: | Ye, Chengjin, Ding, Yi, Wang, Peng, Lin, Zhenzhi |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/151221 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Peak load forecasting using a fuzzy neural network
by: Dash, P.K., et al.
Published: (2014) -
Peak load forecasting using a fuzzy neural network
by: Dash, P.K., et al.
Published: (2014) -
Urban electric load forecasting with mobile phone location data
by: Selvarajoo, Stefan, et al.
Published: (2020) -
A neural network short-term load forecaster
by: Srinivasan, D., et al.
Published: (2014) -
Load and renewable energy forecasting for a microgrid using persistence technique
by: Dutta, Shreya, et al.
Published: (2018)