The impact of wind field spatial heterogeneity and variability on short-term wind power forecast errors-Reference-Cited by-同舟云学术

The impact of wind field spatial heterogeneity and variability on short-term wind power forecast errors

Published:2019-05 Issue:3 Volume:11 Page:033304
ISSN:1941-7012
Container-title:Journal of Renewable and Sustainable Energy
language:en
Short-container-title:Journal of Renewable and Sustainable Energy

Author:

Yang Mao¹,Zhang Luobin¹^ORCID,Cui Yang¹,Yang Qiongqiong²,Huang Binyang³

Affiliation:

1. Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Changchun Street, No. 169, Jilin 132012, China

2. Baoji Power Supply Company of State Grid Shanxi Electric Power Company, Baoji 721004, China

3. State Grid Chongqing Electric Power Supply Company, Maintenance Branch, Chongqing 400015, China

Funder

National Key R&D Program of China

Publisher

AIP Publishing

Subject

Renewable Energy, Sustainability and the Environment

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5064438

Reference40 articles.

1. Forecasting the High Penetration of Wind Power on Multiple Scales Using Multi-to-Multi Mapping

2. Stratification-Based Wind Power Forecasting in a High-Penetration Wind Power System Using a Hybrid Model

3. A Short-Term Wind Power Forecasting Approach With Adjustment of Numerical Weather Prediction Input by Data Mining

4. Novel Multi-Step Short-Term Wind Power Prediction Framework Based on Chaotic Time Series Analysis and Singular Spectrum Analysis

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Predicting wind power generation using machine learning and CNN-LSTM approaches;Wind Engineering;2022-07-21

2. Conditional simulation of 3D nonstationary wind field for sea-crossing bridges;Advances in Structural Engineering;2022-05-18

3. Characterizing Global Sea Surface Local Wind Variability From ASCAT Data;IEEE Transactions on Geoscience and Remote Sensing;2022

4. Ultra Short-Term Wind Power Forecasting Based on Sparrow Search Algorithm Optimization Deep Extreme Learning Machine;Sustainability;2021-09-20

5. Wind power generation prediction in a complex site by comparing different numerical tools;Journal of Wind Engineering and Industrial Aerodynamics;2021-09