人工智能在风能预测中的应用调查

IF 9.7 2区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Archives of Computational Methods in Engineering Pub Date : 2024-09-13 DOI:10.1007/s11831-024-10182-8
Poonam Dhaka, Mini Sreejeth, M. M. Tripathi
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引用次数: 0

摘要

随着清洁能源需求的增加,风能和太阳能等可再生能源预测变得越来越重要。因此,提高风能预测的准确性以确保电力系统的高效、可靠和安全运行至关重要。由于机器学习和深度学习等人工智能(AI)技术的成功,有关风力预测的研究在过去 10 年中急剧增加。尽管人工智能方法潜力巨大,但也充满了不确定性。目前仍不清楚某些因素会如何影响人工智能算法预测的准确性。本研究回顾了人工智能在风能预测中的应用,旨在提供以下方面的分析:(1)基于人工智能的风能预测结构和优化器;(2)确定性和概率性技术的预测性能评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A Survey of Artificial Intelligence Applications in Wind Energy Forecasting

Renewable energy forecasting, such as Wind and Solar forecasting, is becoming more critical as the demand for clean energy increases. Thus, it is crucial to enhance the accuracy of wind power predictions to ensure electrical energy system’s efficient, reliable, and safe operation. Research on wind forecasting has increased dramatically over the past 10 years due to the success of Artificial Intelligence (AI) technologies like machine learning and deep learning. Despite their potential, AI approaches are fraught with uncertainties. It remains unclear how certain factors may influence the accuracy of AI algorithm predictions. This study reviews AI applications in Wind energy forecasting, aiming to provide an analysis of (1) AI-based structures and optimizers for Wind forecasting, (2) forecast performance evaluation for Deterministic and Probabilistic techniques.

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来源期刊
CiteScore
19.80
自引率
4.10%
发文量
153
审稿时长
>12 weeks
期刊介绍: Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.
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