Forecasting household electric appliances consumption and peak demand based on hybrid machine learning approach
Machine learning approaches have diverse applications in forecasting electrical energy consumption using smart meter data. Various classification techniques and clustering methods analyze smart meter data for accurately forecasting the electrical appliance consumption and peak demand. Electrical app...
Main Authors: | Ejaz Ul Haq, Xue Lyu, Youwei Jia, Mengyuan Hua, Fiaz Ahmad |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-12-01
|
Series: | Energy Reports |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484720314967 |
Similar Items
-
Robust Day-Ahead Forecasting of Household Electricity Demand and Operational Challenges
by: Alexis Gerossier, et al.
Published: (2018-12-01) -
Demand Forecasting Tool For Inventory Control Smart Systems
by: Fatima Zohra Benhamida, et al.
Published: (2021-06-01) -
Evolutionary Hybrid System for Energy Consumption Forecasting for Smart Meters
by: Diogo M. F. Izidio, et al.
Published: (2021-03-01) -
Smart Meter Forecasting from One Minute to One Year Horizons
by: Luca Massidda, et al.
Published: (2018-12-01) -
Novel Approaches For Demand Forecasting In Semiconductor Manufacturing
by: Kumar, Chittari Prasanna
Published: (2009)