Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm

Author:

Gao Tian,Niu Dongxiao,Ji ZhengsenORCID,Sun Lijie

Funder

National Key Research and Development Program of China

Ministry of Science and Technology of the People's Republic of China

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference72 articles.

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3. A novel long-term power forecasting based smart grid hybrid energy storage system optimal sizing method considering uncertainties;Zhao;Inf Sci,2022

4. N-BEATS neural network for mid-term electricity load forecasting;Oreshkin;Appl Energy,2021

5. Short-term electricity demand forecasting via variational autoencoders and batch training-based bidirectional long short-term memory;Moradzadeh;Sustain Energy Technol Assessments,2022

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