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meteodyn.com
article
https://meteodyn.com/sectors/onshore-and-offshore-wind-power/meteodyn-univers…
Home » Sectors » Onshore and Offshore Wind » Meteodyn Universe – Wind farm development software suite » Meteodyn WPA. Meteodyn WPA is a wind farm performance analysis software. The software automatically analyzes SCADA data from wind turbines and then presents the data as graphs or combined indicators. Data from wind farms and wind turbines can be analyzed in-depth and in a more understandable way. ## The wind farm performance processing and analysis software. The software automatically detects and classifies the operating status of wind turbines into different categories without the use of turbine status indicators. This feature allows to evaluate the actual power curve of the turbines at the site and to compare it to the manufacturer’s power curve. ### Comparison of wind turbine and wind farm production. Comparison of actual and potential production of wind turbines and wind farms with a monthly and cumulative view for the entire wind farm or for each turbine.
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ul.com
article
https://www.ul.com/software/openwind-wind-farm-modeling-and-layout-design-sof…
# Openwind | Wind Farm Modeling and Layout Design Software. Design wind farms that are more efficient than ever before with Openwind—one of the industry’s most advanced pieces of software for creating and optimizing turbine layouts. Openwind is a wind farm design and optimization software used throughout a wind project’s development to create optimal turbine layouts that maximize energy production, minimize energy losses, account for plant development costs and generate overall project efficiencies. Design wind farms that are optimized for levelized cost of energy with Openwind by UL Solutions. This state-of-the-art software creates turbine layouts to maximize energy production, minimize energy losses, account for development costs and generate overall efficiencies, all on one platform. With Openwind, you can take into account wind resources, wakes, noise, shadow flicker, curtailments, GIS constraints and more. Openwind’s compatibility with other wind software allows you to easily import external wind resource grids and data files into an Openwind project.
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dnv.com
article
https://www.dnv.com/training/a-guide-to-wind-farm-performance-optimization
Wind farm monitoring and data analysis to maximize energy capture. DNV has reviewed the performance of over 1000 wind farms and 50,000 turbines worldwide, including IEC-based power performance testing, availability audits, operational energy assessments, performance monitoring and benchmarking. The course will illustrate how to better monitor availability, power performance, and component health. To complement the warranties and formal procedures (see companion course “Wind Turbine Power Performance IEC 61400-12-1”), wind farm performance may be optimized and tracked through live operations monitoring and periodic detailed analysis. The SCADA data continuously recorded by each turbine and met masts on the wind farm can be interrogated to track performance and monitor the health of turbine components. The course will explain the value of SCADA data and how to leverage this to proactively manage performance. Explore the maritime training courses. ### Energy Academy. Explore the energy training courses. Explore the business assurance training courses. Explore the software training courses.
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clir.eco
article
https://www.clir.eco/blog/beyond-the-dashboard-what-s-going-on-at-your-wind-farm
Clir's software offers an independent view of any changes made to a turbine or farm which enables us to quickly detect new issues and deliver insights faster.
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sciencedirect.com
article
https://www.sciencedirect.com/science/article/abs/pii/S0029801824010436
FLORIS package calculates the optimal yaw misalignment of all wind turbines. · OpenFAST was used to calculate the time series load of the wind turbine tower.
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nature.com
article
https://www.nature.com/articles/s41598-025-27896-9
# Improving wind power prediction with advanced temporal and frequency domain processing combined with error correction. Accurate prediction of wind power is crucial for grid scheduling and the integration of renewable energy, given its significant temporal variability and nonlinear characteristics. This study proposed a multi-module integrated model for wind power forecasting based on time–frequency domain analysis, aiming to enhance prediction accuracy and reliability. The mode9l combined several advanced techniques, including Wavelet Convolutions (WTC), Long Short-Term Memory Networks (LSTM), Time Series Lightweight Adaptive Network (TSLANet), Frequency Enhanced Channel Attention Mechanism (FECAM), and Fast Kolmogorov-Arnold Networks (FastKAN). Each module was designed to capture distinct characteristics in wind power data, such as local frequency features, temporal dependencies, global contextual information, frequency-domain features, and complex nonlinear relationships. Through the integration of these modules, the model achieved high-precision predictions in multi-scale and dynamic environments. Experimental results showed that the model delivered exceptional performance across various test scenarios, significantly improving the handling of multi-scale, complex nonlinear, and global dependency issues in wind power forecasting, demonstrating considerable application potential.
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tethys-engineering.pnnl.gov
official
https://tethys-engineering.pnnl.gov/publications/time-domain-optimization-too…
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nationaloffshorewind.org
article
https://nationaloffshorewind.org/wp-content/uploads/NREL-147506_Final_Report.pdf
Final Report – D5 Wind Farm Control and Layout Optimization for U.S. Offshore Wind Farms Prepared for: National Offshore Wind Research and Development Consortium Christine Sloan, Project Manager Julian Fraize, Project Manager Prepared by: National Renewable Energy Laboratory (NREL) Golden, CO 80401 Paul Fleming Principal Investigator David Dunn NOWRDC Project Coordinator Patrick Duffy, Christopher Bay, Matthew Churchfield Rebecca Barthelmie, Sara Pryor Report Agreement # 147506 FIA-19-16408 February 2023 2 Acronyms and Abbreviations AEP annual energy production BOEM Bureau of Ocean Energy Management CC cumulative curl FLORIS FLOw Redirection and Induction in Steady State GCH Gauss curl hybrid GW gigawatt IEA International Energy Agency LCOE levelized cost of energy MW megawatt nm nautical mile NREL National Renewable Energy Laboratory ORBIT Offshore Renewables Balance-of-System and Installation Tool SCADA supervisory control and data acquisition SOWFA Simulator fOr Wind Farm Applications TI turbulence intensity WRF Weather Research and Forecasting 3 Notice This report was prepared by Paul Fleming in the course of performing work contracted for and sponsored by the National Offshore Wind Research and Consortium (NOWRDC), New York State Energy Research and Development Authority (NYSERDA), and the U.S. Department of Energy (hereafter the “Sponsors”).