Cleaning of Abnormal Wind Speed Power Data Based on Quartile

This paper deeply analyzes the distribution characteristics of abnormal data and proposes a novel method for abnormal data cleaning based on a classification processing framework.

Abnormal Detection of Wind Turbine Operating Conditions Based on

This paper introduces a monitoring method based on state curves and includes a study that analyzes five types of state curves, namely, wind speed–power, wind speed–rotor speed, wind

Wind power anomaly data detection based on unsupervised

Wind power anomaly data detection based on unsupervised methods To cite this article: Hao Zhang et al 2024 J. Phys.: Conf. Ser. 2728 012033 View the article online for updates and enhancements.

A Fault and Capacity Loss Prediction Method of Wind Power Station

Extreme weather events can severely affect the operation and power generation of wind farms and threaten the stability and safety of grids with high penetration of renewable energy.

Image-Based Abnormal Data Detection and Cleaning Algorithm

ata based on wind power curve (WPC) images. The abnormal data are cat-egorized into three types, negative points, scattered points, and stacked points. The proposed algorithm includes three steps,

Abnormal State Analysis of Wind Turbines Based on the Power Curve

For the difficulty of operation and maintenance of wind turbines, anomaly detection technology was derived to identify faults early. In the research of power cu.

Common problems with wind power supply for base stations

Considering the negative resistance effect of power electronic equipment, unstable resonance problems may occur between wind farms and converter stations. This paper focuses on the

An adaptive identification method of abnormal data in wind and solar

Accurate and credible operation data sets of wind and solar power stations are the basis of many research works. However, such data sets often contain abnormal data due to failure,

Protection of Wind Electric Plants

The performance of the WEP during a fault condition is different from that of a traditional generating station [1]. Therefore, the protection considerations for a large WEP will be different than those of a

Wind turbines abnormality detection through analysis of wind farm

In this study, we propose a new abnormality detection and prediction technique based on heterogeneous signals and information, such as output power signals and wind tur-bines downtime