Short‐term probabilistic forecasting for regional wind power using distance‐weighted kernel density estimation-Reference-Cited by-同舟云学术

Short‐term probabilistic forecasting for regional wind power using distance‐weighted kernel density estimation

Published:2018-09-28 Issue:15 Volume:12 Page:1725-1732
ISSN:1752-1416
Container-title:IET Renewable Power Generation
language:en
Short-container-title:IET Renewable Power Generation

Author:

Wang Zhao¹²^ORCID,Wang Weisheng¹,Liu Chun¹,Wang Bo¹,Feng Shuanglei¹

Affiliation:

1. State Key Laboratory of Operation and Control of Renewable Energy & Storage SystemsRenewable Energy Research CenterChina Electric Power Research InstituteBeijingPeople's Republic of China

2. Electrical EngineeringTsinghua UniversityBeijingPeople's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2018.5282

Reference36 articles.

1. One‐day ahead wind speed/power prediction based on polynomial autoregressive model

2. Trading wind energy on the basis of probabilistic forecasts both of wind generation and of market quantities

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

4. Impacts of Dynamic Probabilistic Reserve Sizing Techniques on Reserve Requirements and System Costs

5. A Probabilistic Method for Energy Storage Sizing Based on Wind Power Forecast Uncertainty

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