An effective dimensionality reduction approach for short-term load forecasting-Reference-Cited by-同舟云学术

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An effective dimensionality reduction approach for short-term load forecasting

Published:2022-09 Issue: Volume:210 Page:108150
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Yang Yang^ORCID,Wang Zijin,Gao Yuchao,Wu Jinran^ORCID,Zhao Shangrui^ORCID,Ding Zhe^ORCID

Funder

Nanjing University of Posts and Telecommunications

Wuhan University of Technology

Fundamental Research Funds for the Central Universities

Australian Research Council

Australian Research Council Centre of Excellence for Mathematical and Statistical Frontiers

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Reference56 articles.

1. Intraday wind power forecasting employing feedback mechanism;Gupta;Electr. Power Syst. Res.,2021

2. A novel short-term load forecasting framework based on time-series clustering and early classification algorithm;Chen;Energy Build.,2021

3. An electricity load forecasting model for integrated energy system based on bigan and transfer learning;Zhou;Energy Rep.,2020

4. Ponnuthurai nagaratnam suganthan, and gehan AJ amaratunga. Empirical mode decomposition based ensemble deep learning for load demand time series forecasting;Qiu;Appl. Soft Comput.,2017

5. A reliability-based approach for integrated generation and transmission maintenance coordination in restructured power systems;Moinian;Electr. Power Syst. Res.,2022

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