Simulating wind power forecast error distributions for spatially aggregated wind power plants-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Simulating wind power forecast error distributions for spatially aggregated wind power plants

Published:2019-09-11 Issue:1 Volume:23 Page:45-62
ISSN:1095-4244
Container-title:Wind Energy
language:en
Short-container-title:Wind Energy

Author:

Miettinen Jari¹^ORCID,Holttinen Hannele¹^ORCID,Hodge Bri‐Mathias²³^ORCID

Affiliation:

1. Design and Operation of Energy SystemsVTT ‐ Technical Research Centre of Finland Espoo Finland

2. Power System Design and StudiesNational Renewable Energy Laboratory, NREL Denver Colorado USA

3. Computer and Energy EngineeringUniversity of Colorado Boulder Boulder Colorado USA

Funder

Academy of Finland

Publisher

Wiley

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.2410

Reference34 articles.

1. Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power

2. Setting the Operating Reserve Using Probabilistic Wind Power Forecasts

3. Towards Improved Understanding of the Applicability of Uncertainty Forecasts in the Electric Power Industry

4. Improving Renewable Energy Forecasting With a Grid of Numerical Weather Predictions

5. Current methods and advances in forecasting of wind power generation

Cited by 12 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. Short‐Term Offshore Wind Power Prediction Based on Significant Weather Process Classification and Multitask Learning Considering Neighboring Powers;Wind Energy;2024-07-11

2. Efficient Scenario Generation for Chance-Constrained Economic Dispatch Considering Ambient Wind Conditions;IEEE Transactions on Power Systems;2024-07

3. Investigation of hydraulic losses in different clocking positions of pump-turbine in pump mode;Journal of Energy Storage;2024-03

4. Review on bidding strategies for renewable energy power producers participating in electricity spot markets;Sustainable Energy Technologies and Assessments;2023-08

5. Short‐term wind power prediction based on stacked denoised auto‐encoder deep learning and multi‐level transfer learning;Wind Energy;2023-07-13

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3