A weighted integrated forecasting approach based on VMD decomposition reconstruction for high energy-consuming loads

Author:

Gel Junxiong1,Liu Chuang1,Yuan Fusheng2,Zhao Tianshuo3,Meng Fanbo4,Li Yujia5

Affiliation:

1. School of Electrical Engineering Northeast Electric Power University,Jilin,China,132012

2. Beijing Zhixin Microelectronics Technology Co., LTD,Beijing,China,102200

3. McMaster University,Ontario,Canada,1280

4. State Grid Liaoning Electric Power Company Limited,Shenyang,China,110002

5. China Electric Power Research Institute,Department of Civil,Beijing,China,100192

Publisher

IEEE

Reference6 articles.

1. Annual industrial and commercial heat load profiles: modeling based on k-Means clustering and regression analysis, Energy Convers;Jesper;Manage.: X,2021

2. Daily load profiles clustering: a powerful tool for demand side management in medium-sized industries;Richard;ACEEE Summer Study on Energy Efficiency in Industry,2017

3. Synthetic hourly electricity load data for the paper and food industries;Valdes;Data Brief,2021

4. Fuzzy C-means clustering applied to load profiling of industrial customers, Electr;Dedic;Power Compon. Syst,2022

5. Time- and component-resolved energy system model of an electric steel mill;Dock;Clean. Eng. Technol.,2021

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