This introductory session discusses the intersection of wind energy and climate change. It explores global wind trends, extreme weather events, and the influence of sea surface temperature anomalies, raising critical questions about how these factors affect wind energy resource assessments and production.

In this presentation, Tristan Hauser uses a case study to show how climate change is impacting wind energy. He discusses the challenges of predicting impacts at specific locations and highlights uncertainties in climate models and the need for comprehensive data.

In this session, Nathan Lehmen applies data collected from ERA5 to analyze its impact on wind energy projects. He explores how the incorporation of ERA5 data has affected long-term wind speed estimates, increased uncertainty in project forecasting, and ultimately reduced potential revenue. Nathan compares this new dataset to previous data sources, like Merit 2, across various locations and discusses strategies, such as ensemble correlations, to address sudden data changes.

In this session, Atmospheric Scientist Jennifer Newman discusses the significance of wind anomalies in wind resource assessment. The session explores the distinction between wind anomalies and site-specific generation anomalies, emphasizing the need for multiple reanalysis data sets for a more comprehensive analysis.

The video features Anna Lopez, co-founder of Climate Scale, discussing methodologies to quantify climate change risk in wind resources. She emphasizes understanding past wind speed variability to project future changes and explores the use of storylines to address uncertainties in climate models.

This introductory session discusses how to maximize the potential of installed wind assets through operational assessments and repowering. Topics include modifications or repowering, adding solar capacity, measuring production increases, and evaluating SCADA data to identify generation improvements.

In this session, Brian Kramak discusses the AWEA TR1 document, a technical report focused on wind plant power measurement and performance analysis. It utilizes methodologies from the OpenOA platform for operational assessments using SCADA data.

This session highlights how combining wind and solar can lead to better performance and explores factors that impact decision-making for future energy projects, including potential agreements with energy buyers.

This session covers two methods for evaluating performance changes in wind projects: the power curve method and the conditional power method. The power curve method involves collecting wind and power data to estimate annual energy production (AEP) with low uncertainty, though it is limited to flat terrains and fewer turbines. The conditional power method compares power production before and after enhancements, using a control turbine, and applies to more turbines but with higher uncertainty. Combining both methods increases confidence in performance evaluations.

This video covers SCADA-based energy assessments and the use of machine learning to analyze operational data from wind farms. It explains The benefits of using machine learning algorithms for efficiency and accuracy, along with energy assessment methods and their application in repowering projects.

This  Q&A session discusses the use of machine learning models in various wind energy projects and environments. It covers topics such as the benefits of site-specific training datasets, handling uncertainty with ensemble approaches, and the impact of additional clipping in hybrid energy scenarios.

This video presents an in-depth look at wind farm blockage and induction zone effects on energy production. It reviews the history and research on the topic, using LiDAR images and numerical simulations to explore causes of underperformance.

This session takes an analytical approach to understanding cumulative induction zone effects in wind farms. It examines how the induction zone from one turbine, along with those from other turbines, impacts wind fields and energy yield. 

This video covers the effects of turbine interaction in wind energy, focusing on how adding or removing turbines impacts wind speed and downstream effects. It highlights the importance of understanding both blockage and downstream impacts and stresses the need for comprehensive measurement campaigns to improve insights into turbine interaction and overall wind farm performance.

This session addresses wake effects in wind resource campaigns, focusing on a case study involving a 60-meter tower near a wind project. It explores the wake impacts on measurement data and proposes a correction method that accounts for wind speed deficits, turbulence intensity, and directional variations.

This session explores atmospheric interactions and their impact on energy loss in wind farms. It argues that with the increasing size of turbines, traditional wake loss models are insufficient, and the talk explores how factors like flow acceleration, blockage, and atmospheric changes affect energy losses.

This session compares Floating LiDAR in offshore wind measurement to Met Masts, focusing on the importance of accurate wind resource assessment and cost reduction. The presentation recommends combining both for performance verification and highlights the growing use of Floating LiDAR in the industry as a viable offshore measurement option.

This video covers the meteorological impacts on LiDAR calibration, focusing on the new IEC 61412-1 standard for remote sensing devices in wind performance tests. The study looks at how factors like wind shear and turbulence affect LiDAR accuracy and suggests the need for a new averaging method in high-turbulence areas before discussing plans to expand tests to other sites and LiDAR models.

This session covers the use of scanning LiDAR devices in the wind energy industry to solve operational challenges. The presentation explores the progression of remote sensing technology and the cost-effectiveness of scanning LiDAR for commercial use, emphasizing its role in improving wind-turbine interactions and operational efficiency in the field.

This session focuses on remote sensing corrections in complex terrain, introducing CFARS and their efforts to standardize remote sensing devices. It highlights complex flow correction techniques, which combine remote sensor data with computational fluid dynamics (CFD) models to reduce biases and uncertainties in wind estimates.

This video discusses the challenges and advancements in remote sensing for wind energy, focusing on pulse-based LiDAR systems for high-frequency measurements. It introduces a virtual LiDAR simulator for testing scanning strategies and designing next-generation systems and highlights the critical role of precise measurements, especially for offshore wind energy applications.

This video features a panel discussion on various advancements and challenges in LiDAR technology. Topics include wind speed correction, the reliability and data coverage of floating LiDAR offshore, and improvements in the range and cost-effectiveness of scanning LiDAR devices.

This session discusses the use of LiDAR technology for power performance measurements in wind turbines, focusing on ground-based and nacelle-mounted LiDAR. It highlights the advantages of LiDAR in providing fast and accurate power curve testing, along with the challenges and considerations involved.

This video provides an overview of various initiatives related to power curve measurement in the energy sector. It covers the roles of organizations like the IEA, IEC, and Carbon Trust in reducing barriers to the commercial use of remote sensing devices (RSDs).

This presentation discusses the use of LiDAR in power performance testing for wind turbines, emphasizing its role in maximizing return on investment and maintaining turbine consistency. It highlights the benefits of LiDAR, emphasizing its flexibility, providing accurate power curves, and monitoring long-term performance. The presentation also discusses the shift toward data-driven approaches and the value of non-contractual performance tests.

This presentation provides an overview of power performance testing in the wind energy industry. It offers strategies for managing uncertainties in testing, including careful test planning and contractual considerations, and emphasizes the benefits of using remote sensing devices for improved cost and safety in power performance evaluations.

This video introduces CFARS (Consortium for Advancing Remote Sensing), a platform that promotes the use of remote sensing devices in the wind industry. Made up of over 30 companies, CFARS focuses on sharing information, creating standards, and lowering project costs.

This video covers offshore power performance testing, focusing on using power curves from remote sensing devices and the key variables in multi-dimensional power curves. It highlights variables like turbulence, wind speed, and temperature that impact power output, and stresses the importance of identifying the main factors affecting performance and more intentional industry collaboration. 

This session provides an overview of the work being done by the CFARS Site Suitability Subgroup to improve the understanding and accuracy of turbulence intensity measurements from remote sensing devices. The group explores adjustment methods and atmospheric influences, aiming to offer data-driven insights and refine industry practices around TI measurement accuracy and bias.

This video covers wind turbine site suitability from the OEM perspective, focusing on the importance of customer-provided site data and compliance with building codes. The session highlights the need for collaboration between OEMs and customers to align on assessments and maximize value.

This video presents research on how wind project performance changes over time in the United States. The study of 917 wind plants shows that newer plants experience minimal performance decline in their first 10 years, while older plants see a mild decline, particularly after the expiration of the production tax credit. Technological advancements, such as better turbines and sensors, have contributed to improved performance in newer plants.

This session explains power curve inner and outer range mapping in the wind industry, focusing on how these ranges affect power production. It discusses the growing complexity of power curves due to larger turbines and highlights the importance of understanding uncertainty in both ranges.

This video covers a panel discussion on key areas of research and process improvements in turbine suitability. The panelists highlight the challenge of limited public wind speed data and explore the potential of new public datasets.

This video explains how time series energy modeling is used to assess plant losses and operations in wind power projects. The presentation shares results from two studies showing the strong correlation between modeled and real power generation and demonstrates the benefits of applying loss estimates across different wind farms. 

This presentation covers time series modeling for hedge scenarios, showing the limitations of using P99s for hedge volumes and the need for more detailed analysis. It emphasizes the benefits of time series modeling for making better decisions on hedge volume and pricing.

This session covers time series wind resource assessment, explaining how to accurately create production time series data for renewable energy projects. It discusses how different types of losses—like wakes, curtailment, and turbine performance—interact and should be applied in sequence and emphasizes the importance of considering time-variant losses for better energy production estimates.

The session explores how solar and wind energy can work together to create a more reliable and efficient renewable energy system. It discusses the complementary nature of these energy sources and highlights the advantages of combining resources together to maximize energy production. 

This video focuses on time series modeling and analysis in the renewable energy sector. The discussion covers expanding analysis to include more projects, how market trends are influencing methods, and the need for tailoring modeling approaches to specific use cases.