The latent state hazard model, with application to wind turbine reliability

Application of a new information priority accumulated grey model with time power to predict short-term wind turbine capacity

Wind energy makes a significant contribution to global power generation. Predicting wind turbine capacity is becoming increasingly crucial for cleaner production. For this purpose, a new information priority accumulated grey model with time power is proposed to predict short-term wind turbine capacity. Firstly, the computational formulas for the time response sequence and the prediction values are deduced by grey modeling technique and the definite integral trapezoidal approximation formula. Secondly, an intelligent algorithm based on particle swarm optimization is applied to determine the opt…

基于Copula变分推断的序列不完整风电曲线定向监测方法

A Directional Monitoring Approach of Sequential Incomplete Wind Power Curves with Copula-based Variational Inference

针对风速波动导致不同时段功率曲线难以比较的问题，提出基于Copula变分推断的序列不完整风电曲线定向监测方法，经英国风电场数据验证，可提升建模精度与退化监测效果。

基于代理模型的浮式海上风力机长期疲劳损伤估算研究

On long-term fatigue damage estimation for a floating offshore wind turbine using a surrogate model

本研究针对浮式海上风力机长期疲劳损伤估算效率低的问题，提出基于高斯过程回归的代理模型框架，通过少量代表性海况结合补充海况实现高效收敛，经5-MW半潜式风机验证，可在保证精度的同时减少大量响应仿真。

用于从稀疏气象数据中估计未监测站点风力机高度风速的两步时空框架

A Two-Step Spatio-Temporal Framework for Turbine-Height Wind Estimation at Unmonitored Sites from Sparse Meteorological Data

本文提出了一种两步时空框架，利用稀疏气象数据实时估计风电场风速，提升风能资源评估精度。

Measuring Wind Turbine Health Using Drifting Concepts

Time series processing is an essential aspect of wind turbine health monitoring. Despite the progress in this field, there is still room for new methods to improve modeling quality. In this paper, we propose two new approaches for the analysis of wind turbine health. Both approaches are based on abstract concepts, implemented using fuzzy sets, which summarize and aggregate the underlying raw data. By observing the change in concepts, we infer about the change in the turbine's health. Analyzes are carried out separately for different external conditions (wind speed and temperature). We extract …

用于风电分布的双机制统计框架：从风速波动到涡轮机控制

A Two-Regime Statistical Framework for Wind-Power Distributions: From Wind-Speed Fluctuations to Turbine Control

研究风电变异性挑战，开发双机制统计框架。在空气动力学运行状态下推导风电分布解析表达式，在控制主导的近额定状态下表征功率亏缺，为风力涡轮机全运行范围的风电波动提供物理解释统计描述。

风力涡轮机 SCADA 数据相关矩阵的非平稳性及其对故障检测的启示

Non-stationarity in correlation matrices for wind turbine SCADA-data and implications for failure detection

该研究分析 Thanet 海上风电场高频 SCADA 数据，利用移动窗口 Pearson 相关矩阵与聚类识别由风速和控制系统决定的运行状态，为故障检测提供考虑非平稳性的自动化预处理框架。

Reconstructing the intermittent dynamics of the torque in wind turbines

We apply a framework introduced in the late nineties to analyze load measurements in off-shore wind energy converters (WEC). The framework is borrowed from statistical physics and properly adapted to the analysis of multivariate data comprising wind velocity, power production and torque measurements, taken at one single WEC. In particular, we assume that wind statistics drives the fluctuations of the torque produced in the wind turbine and show how to extract an evolution equation of the Langevin type for the torque driven by the wind velocity. It is known that the intermittent nature of the a…

设备健康评估：用于风力涡轮机性能的时间序列分析

Equipment Health Assessment: Time Series Analysis for Wind Turbine Performance

本文基于多台风机 SCADA 数据，融合 FNN 与 LSTM 进行功率预测和性能退化检测，证明集成模型及按风机自动定制建模的优越性与跨设备推广价值。

自动化拟合数据集的危险：风力涡轮机成本模型的案例

The perils of automated fitting of datasets: the case of a wind turbine cost model

本文研究了自动化回归分析在风力涡轮机成本模型中的应用问题，提出了一个针对特定地点的投资成本模型，但认为通用成本模型存在缺陷，可能导致其他应用场景中出现不合理结果。