Jan Helsen
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View article: Scalable SCADA-driven failure prediction for offshore wind turbines using autoencoder-based NBM and fleet-median filtering
Scalable SCADA-driven failure prediction for offshore wind turbines using autoencoder-based NBM and fleet-median filtering Open
Offshore wind turbines are crucial for sustainable energy production but face significant challenges in operational reliability and maintenance costs. In particular, the scalability and practicality of failure detection systems are a key c…
View article: Precipitation Conditions in Offshore Wind Farm Zones: Insights from Satellites and Weather Simulations
Precipitation Conditions in Offshore Wind Farm Zones: Insights from Satellites and Weather Simulations Open
Characterizing wind and precipitation conditions is essential for the durability and maintenance of wind turbine components. Precipitation-driven leading edge erosion of turbine blades has emerged as a significant concern, as it compromise…
View article: An assessment of the metocean conditions in the Belgian offshore zone
An assessment of the metocean conditions in the Belgian offshore zone Open
This paper investigates the performance of two wind speed databases (NORA3 and ERA5) for wind resource assessment in an offshore wind farm located in the Belgian Exclusive Economic Zone. A combination of data from ERA5 and NORA3, SCADA and…
View article: Condition monitoring of wind turbine drivetrains: State-of-the-art technologies, recent trends, and future outlook
Condition monitoring of wind turbine drivetrains: State-of-the-art technologies, recent trends, and future outlook Open
As wind energy scales up to meet global decarbonization and energy security goals, reducing the LCoE has become essential, particularly through improvements in O&M. This positioning paper explores the state-of-the-art in condition moni…
View article: Leveraging signal processing and machine learning for automated fault detection in wind turbine drivetrains
Leveraging signal processing and machine learning for automated fault detection in wind turbine drivetrains Open
Wind energy is considered a sustainable renewable energy source; however, it faces the challenge of significant operating and maintenance costs. The research proposes a hybrid fault detection method to combine the physical domain knowledge…
View article: A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data
A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data Open
Wind farm performance monitoring has traditionally relied on deterministic models, such as power curves or machine learning approaches, which often fail to account for farm-wide behavior and the uncertainty quantification necessary for the…
View article: The BeFORECAST project – wind power forecasting for the Belgian offshore wind farms
The BeFORECAST project – wind power forecasting for the Belgian offshore wind farms Open
The BeFORECAST project (2022 – 2025) is a research project on wind power forecasting for Belgian offshore wind farms funded by the Energy Transition Funds of the Federal Public Service Economy, SMEs, Middle Classes, and Energy of the Belgi…
View article: Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data
Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data Open
This paper introduces a novel model for predicting wind turbine power output in a wind farm at a high temporal resolution of 30 s. The wind farm is represented as a graph, with graph neural networks (GNNs) used to aggregate selected input …
View article: Day-Ahead Bidding Strategies for Wind Farm Operators Under a One-Price Balancing Scheme
Day-Ahead Bidding Strategies for Wind Farm Operators Under a One-Price Balancing Scheme Open
View article: Optimal day-ahead trading and power control for a hybrid wind-hydrogen plant with multi-agent reinforcement learning
Optimal day-ahead trading and power control for a hybrid wind-hydrogen plant with multi-agent reinforcement learning Open
Hybrid wind-hydrogen plants have multiple revenue sources, subject to uncertainties and trade-offs. As a consequence, maximizing their overall profitability is a challenging optimization problem. Since electricity is typically traded in ad…
View article: A comparison between scanning LiDAR and scada-based hyperparameter tuning of analytical wake models
A comparison between scanning LiDAR and scada-based hyperparameter tuning of analytical wake models Open
Proper calibration of engineering wake models is essential to accurately estimate the energy yield of wind farms. This study has as main goal to calibrate analytical wake models using two different data sources, i.e. scanning LiDAR and sca…
View article: Scalable SCADA-driven Failure Prediction for Offshore Wind Turbines Using Autoencoder-Based NBM and Fleet-Median Filtering
Scalable SCADA-driven Failure Prediction for Offshore Wind Turbines Using Autoencoder-Based NBM and Fleet-Median Filtering Open
Offshore wind turbines are crucial for sustainable energy production but face significant challenges in operational reliability and maintenance costs. In particular, the scalability and practicality of failure detection systems are a key c…
View article: Day-Ahead Bidding Strategies for Wind Farm Operators under a One-Price Balancing Scheme
Day-Ahead Bidding Strategies for Wind Farm Operators under a One-Price Balancing Scheme Open
We study day-ahead bidding strategies for wind farm operators under a one-price balancing scheme, prevalent in European electricity markets. In this setting, the profit-maximising strategy becomes an all-or-nothing strategy, aiming to take…
View article: Power Prediction in Offshore Wind Farms using Transferable Multi-Task Graph Neural Networks
Power Prediction in Offshore Wind Farms using Transferable Multi-Task Graph Neural Networks Open
This study introduces a transferable Graph Neural Network (GNN)-based model for potential power prediction. By encoding the wind farm as a graph, the GNN captures complex spatial relationships and aggregates information from neighboring tu…
View article: Modular deep learning approach for wind farm power forecasting and wake loss prediction
Modular deep learning approach for wind farm power forecasting and wake loss prediction Open
Power production of offshore wind farms depends on many parameters and is significantly affected by wake losses. Due to the variability in wind power and its rapidly increasing share in the total energy mix, accurate forecasting of the pow…
View article: POD-Based Sparse Stochastic Estimation of Wind Turbine Blade Vibrations
POD-Based Sparse Stochastic Estimation of Wind Turbine Blade Vibrations Open
This study presents a framework for estimating the full vibrational state of wind turbine blades from sparse deflection measurements. The identification is performed in a reduced-order space obtained from a Proper Orthogonal Decomposition …
View article: Video-based diagnosis of a rolling element bearing using a high-speed camera: Feedback on the Survishno 2023 conference contest
Video-based diagnosis of a rolling element bearing using a high-speed camera: Feedback on the Survishno 2023 conference contest Open
View article: Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW
Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW Open
Accurately assessing wind turbine performance in large offshore wind farms requires a nuanced understanding of how inflow parameters—turbulence intensity (TI), wind shear, and wind veer—affect power production across different turbine rows…
View article: System identification of offshore wind turbines for model updating and validation using field measurements
System identification of offshore wind turbines for model updating and validation using field measurements Open
This study presents an applied system identification approach for developing, updating, and validating simulation models of wind turbines using field measurements. This is demonstrated by developing a model of a bottom-fixed offshore turbi…
View article: Wind turbine blade root and blade bearing fatigue damage estimation based on field data
Wind turbine blade root and blade bearing fatigue damage estimation based on field data Open
This study investigates the relationship between inflow properties of offshore wind turbines and fatigue damage accumulation in key machine components, specifically focusing on blade root and blade bearing fatigue. It showcases how LiDAR m…
View article: Assessing the impact of wind profiles at offshore wind farm sites for field data-enabled design
Assessing the impact of wind profiles at offshore wind farm sites for field data-enabled design Open
As wind turbines grow and wind farms become denser, more insight into real metocean conditions is essential for operational efficiency and load assessment. Light Detection And Ranging LiDAR) technology, which can substitute the use of mete…
View article: Day-Ahead Trading and Power Control for Hybrid Wind-Hydrogen Plants with Multi-Agent Reinforcement Learning
Day-Ahead Trading and Power Control for Hybrid Wind-Hydrogen Plants with Multi-Agent Reinforcement Learning Open
View article: Leveraging Signal Processing and Machine Learning for Automated Fault Detection in Wind Turbine Drivetrains
Leveraging Signal Processing and Machine Learning for Automated Fault Detection in Wind Turbine Drivetrains Open
Wind energy is considered a sustainable renewable energy source; however, it faces the challenge of significant operating and maintenance costs. The research proposes a hybrid fault detection method to combine the physical domain knowledge…
View article: Insights in wind field reconstruction from two nacelles’ LiDAR in the same offshore wind farm
Insights in wind field reconstruction from two nacelles’ LiDAR in the same offshore wind farm Open
The global rise in offshore wind farms underscores the need to cut costs and optimise energy production. As turbines increase in size and wind farms become more concentrated, mitigating downstream wake effects is crucial for operational ef…
View article: Experimental investigation of the relation between operating conditions and offshore wind turbine drivetrain dynamics
Experimental investigation of the relation between operating conditions and offshore wind turbine drivetrain dynamics Open
This study investigates the impact of operating and environmental conditions on the vibration induced on an offshore wind turbine drivetrain. Furthermore, it explores the role of the dynamic response of the global wind turbine structure to…
View article: Modeling of rain-induced erosion of wind turbine blades within an offshore wind cluster
Modeling of rain-induced erosion of wind turbine blades within an offshore wind cluster Open
This study investigates the influence of wind turbine wakes on the incubation period of leading-edge erosion in offshore environments within an offshore wind cluster. The analysis is performed on a cluster of 250MW+ offshore wind farms mai…
View article: Spatio-Temporal Graph Neural Networks for Power Prediction in Offshore Wind Farms Using SCADA Data
Spatio-Temporal Graph Neural Networks for Power Prediction in Offshore Wind Farms Using SCADA Data Open
This paper introduces a novel model for predicting wind turbine power output within a wind farm at a high temporal resolution of 30 seconds. The wind farm is represented as a graph, with Graph Neural Networks (GNNs) used to aggregate selec…
View article: Modular deep learning approach for wind farm power forecasting and wake loss prediction
Modular deep learning approach for wind farm power forecasting and wake loss prediction Open
Power production of offshore wind farms depends on many parameters and is significantly affected by wake losses. Due to the variability of wind power and its rapidly increasing share in the total energy mix, accurate forecasting of the pow…
View article: Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm
Hyperparameter tuning framework for calibrating analytical wake models using SCADA data of an offshore wind farm Open
This work presents a robust methodology for calibrating analytical wake models, as demonstrated on the velocity deficit parameters of the Gauss–curl hybrid model using 4 years of time series supervisory control and data acquisition (SCADA)…
View article: Investigating North Sea Precipitation Variability: Implications for Offshore Wind Energy Siting and Condition Assessments
Investigating North Sea Precipitation Variability: Implications for Offshore Wind Energy Siting and Condition Assessments Open
Rain-driven wind turbine blade erosion, particularly in offshore locations, has been observed as early as within 5 to 7 years of turbine operation, which is below the lifetime expectancy design age of 20 to 25 year. Due to the harsh atmosp…