A wind power forecasting model based on data decomposition and cross-attention mechanism with cosine similarity-Reference-Cited by-同舟云学术

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A wind power forecasting model based on data decomposition and cross-attention mechanism with cosine similarity

Published:2024-04 Issue: Volume:229 Page:110156
ISSN:0378-7796
Container-title:Electric Power Systems Research
language:en
Short-container-title:Electric Power Systems Research

Author:

Jiang Li,Wang Yifan^ORCID

Publisher

Elsevier BV

Reference44 articles.

1. Approaches to wind power curve modeling: a review and discussion;Wang;Renew. Sustain. Energy Rev.,2019

2. Data processing strategies in wind energy forecasting models and applications: a comprehensive review;Liu;Appl. Energy,2019

3. Current status and future advances for wind speed and power forecasting;Jung;Renew. Sustain. Energy Rev.,2014

4. Deterministic and probabilistic wind speed forecasting with de-noising-reconstruction strategy and quantile regression based algorithm;Hu;Renew. Energy,2020

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

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1. Attack-resilient framework for wind power forecasting against civil and adversarial attacks;Electric Power Systems Research;2025-01

2. A reconstruction-based secondary decomposition-ensemble framework for wind power forecasting;Energy;2024-11

3. Short-term integrated forecasting method for wind power, solar power, and system load based on variable attention mechanism and multi-task learning;Energy;2024-09

4. Short-Term Wind Power Prediction Based on Feature-Weighted and Combined Models;Applied Sciences;2024-08-31

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