SHORT-TERM FORECASTING OF REGIONAL WIND POWER BASED ON CEEMD-FE-ISSA-LSTM ASSOCIATED WITH INVERSE GRAY CLOUD SIMILAR DAYS, 36-45.

A short-term prediction method for wind and solar power is proposedbased on complementary ensemble empirical mode decomposition(CEEMD), fuzzy entropy (FE), improved sparrow search algorithm(ISSA), and long short-term memory network (LSTM).

Authors

Yongqing Zhu (ORCID: https://orcid.org/0000-0003-0092-5743)
Zhaofeng Zhang (ORCID: https://orcid.org/0000-0003-1797-7507)
Qingsheng Li
Zhen Li (ORCID: https://orcid.org/0009-0008-5232-3414)

Publication Details

Journal: International Journal of Power and Energy Systems
Published: 2025-01-01
DOI: https://doi.org/10.2316/j.2025.203-0584
Citations: 1
Primary Topic: Energy Load and Power Forecasting
Type: article
Field-Weighted Citation Impact: 0.73

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article

SHORT-TERM FORECASTING OF REGIONAL WIND POWER BASED ON CEEMD-FE-ISSA-LSTM ASSOCIATED WITH INVERSE GRAY CLOUD SIMILAR DAYS, 36-45.

Yongqing Zhu, Zhaofeng Zhang, Qingsheng Li, Zhen Li

Jan 1, 2025

1 citations

International Journal of Power and Energy Systems

Energy Load and Power Forecasting

0.73

article

SHORT-TERM FORECASTING OF REGIONAL WIND POWER BASED ON CEEMD-FE-ISSA-LSTM ASSOCIATED WITH INVERSE GRAY CLOUD SIMILAR DAYS, 36-45.

Yongqing Zhu, Zhaofeng Zhang, Qingsheng Li, Zhen Li

January 1, 2025article en

1 citations

Abstract

International Journal of Power and Energy SystemsVol. 45(1)

Affordable and clean energy

Openalex Percentile: Top 27%

Energy Load and Power Forecasting

0.73

DOI Source OpenAlex

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SHORT-TERM FORECASTING OF REGIONAL WIND POWER BASED ON CEEMD-FE-ISSA-LSTM ASSOCIATED WITH INVERSE GRAY CLOUD SIMILAR DAYS, 36-45. — Yongqing Zhu, Zhaofeng Zhang, et al. · International Journal of Power and Energy Systems (2025) | TGRS Research Map | TGRS