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DOE OSTI2023

On the Low Risk of SSR in Type III Wind Turbines Operating in Grid-Forming Control: Preprint

We have shown in a previous work that the risk of sub-synchronous resonance (SSR) between a wind power plant with Type III wind turbines and series-compensated transmission lines is low when the wind turbines in the plant are operated in grid-forming mode, instead of the standard grid-following mode. The fundamental mechanism behind the improved damping characteristics is explained in this paper by modeling the positive and negative sequence impedances of Type III wind turbines for GFM operation mode. It is discovered that the GFM control naturally acts against the negative resistance of Type III wind turbines that results from an interaction between the proportional gain of the rotor-side converter current controller and negative slip. The developed sequence impedance models and improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the sequence impedance response of a 2.5-MW Type III wind turbine during operation in GFL and GFM modes.

grid-following turbine↗

DOE OSTI2024

Grid Integration of Offshore Wind Power: Standards, Control, Power Quality and Transmission

Offshore wind is expected to be a major player in the global efforts toward decarbonization, leading to exceptional changes in modern power systems. Understanding the impacts and capabilities of the relatively new and uniquely positioned assets in grids with high integration levels of inverter-based resources, however, is lacking, raising concerns about grid reliability, stability, power quality, and resilience, with the absence of updated grid codes to guide the massive deployment of offshore wind. To help fill the gap, this paper presents an overview of the state-of-the-art technologies of offshore wind power grid integration. First, the paper investigates the most current grid requirements for wind power plant integration, based on a harmonized European Network of Transmission System Operators (ENTSO-E) framework and notable international standards, and it illuminates future directions. The paper discusses the wind turbine and wind power plant control strategies, and new control approaches, such as grid-forming control, are presented in detail. The paper reviews recent research on the ancillary services that offshore wind power plants can potentially provide, which, when harmonized, will not only comply with regulations but also improve the value of the asset. The paper explores topics of wind power plant harmonics, reviewing the latest standards in detail and outlining mitigation methods. The paper also presents stability analysis methods for wind power plants, with discussions centered on validity and computational efficiency. Finally, the paper discusses wind power plant transmission solutions, with a focus on high-voltage direct-current topologies and controls.

17 WIND ENERGY↗

DOE OSTI2025

Land-Based Wind Reference Architecture

This report describes a summary and the final deliverables for the Wind Reference Architecture project funded by the Department of Energy's (DOE) Wind Energy Technology Office (WETO). The project objective was to further refine the reference architecture of the existing wind power plant reference architecture developed by Idaho National Laboratory (INL) and Sandia National Laboratories (SNL) by expanding the wind turbine generator (WTG) into a separate individual wind turbine reference architecture. Additional details regarding the wind turbine system and how it integrates with a wind power plant were researched and reflected in the reference architecture. This addition is important because it allows researchers to understand the components and devices in a wind turbine, how they function and how a wind turbine integrates into a wind power plant to be able to perform cybersecurity evaluations on the system. The communication and control systems were the focus while developing this reference architecture to understand the cybersecurity posture of a wind turbine and power plant. The information technology (IT) and operational technology (OT) systems perspective are integral in helping improve the cybersecurity posture by creating a starting point to study how wind energy can be safely designed and deployed in our power grid from an integrated systems standpoint. A holistic wind power plant and turbine reference architecture and simulation was developed and made open-sourced for further research efforts.

17 WIND ENERGY↗

DOE OSTI2021

Reliability‐based layout optimization in offshore wind energy systems

Abstract Existing methods for optimizing wind array layouts typically use power or cost objectives and rarely consider reliability‐based objectives. Component and system failure rates, however, are dependent on location‐specific wind conditions, are influenced by array layout and wake interactions, and have a direct and significant impact on capital costs, operational costs, and power production. Although wind power plant models exist that calculate wind loads with sufficient resolution to capture component loading dynamics from wind conditions, they are computationally expensive and thus not suitable for research applications requiring many evaluations, particularly optimization. This study describes the development of computationally efficient, reliability‐based layout optimization methods, enabling us to explore the relationship between component reliability and layout optimization. These methods include the surrogate modeling of the planet bearing life based on varying wind conditions simulated in FAST.Farm and the formulation of reliability‐based objectives based on failure cost and power production models. Through demonstration of this method, we explore how wind conditions, objective functions, and capacity density influence reliability‐based layout optimization. Results indicate that considering reliability alongside power production can reduce failure costs associated with replacement costs and downtime while maintaining or improving power production. Our conclusions highlight the opportunity for wind power plant developers to integrate reliability and operational expenditures alongside performance and capital expenditure objectives in plant design and development to improve plant performance and costs.

17 WIND ENERGY↗

DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗

DOE OSTI2024

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

17 WIND ENERGY↗

DOE OSTI2024

WE-Validate: An Open-Source Framework For Wind Power Validation

Grid operators rely on historical weather time series at existing and planned wind power plants to make informed decisions when planning for a future power grid with very high penetration of renewable power. While synthetic wind power time series have been developed based on historical weather models, their validation with actual power production data remains complex due to variations in modeling practices and methodologies. This paper introduces the WE-Validate framework, originally designed for wind speed validation and now enhanced for wind power validation with a graphical user interface to support users with minimal programming experience. Validation of wind power with WE-Validate is based on robust metrics consisting of RMSE, centered RMSE, average bias, average percent bias, mean absolute error, mean absolute percent error, cross correlation, and calculation of ramping magnitude, rate, and duration. This paper showcases WE-Validate with validation of synthetically derived power for a wind plant in Washington state for one month in 2018. Validation of the synthetic power from two comparison data sets compared with observations shows both comparison series have strong correlation with observed across weekly and monthly aggregations while suffering from persistent negative bias. The suite of metrics within WE-Validate facilitates immediate insight into the utility of the comparison data sets through compression across multiple axes. This user-friendly, open-source tool can be extended beyond wind power, making it a valuable resource for system planners and operators in different domains.

Moncheur de Rieudotte, Malcolm P.↗

DOE OSTI2021

The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows

Abstract. Wind turbine wake models typically require approximations, such as wake superposition and deflection models, to accurately describe wake physics. However, capturing the phenomena of interest, such as the curled wake and interaction of multiple wakes, in wind power plant flows comes with an increased computational cost. To address this, we propose a new hybrid method that uses analytical solutions with an approximate form of the Reynolds-averaged Navier–Stokes equations to solve the time-averaged flow over a wind plant. We compare results from the solver to supervisory control and data acquisition data from the Lillgrund wind plant obtaining wake model predictions which are generally within 1 standard deviation of the mean power data. We perform simulations of flow over the Columbia River Gorge to demonstrate the capabilities of the model in complex terrain. We also apply the solver to a case with wake steering, which agreed well with large-eddy simulations. This new solver reduces the time – and therefore the related cost – it takes to simulate a steady-state wind plant flow (on the order of seconds using one core). Because the model is computationally efficient, it can also be used for different applications including wake steering for wind power plants and layout optimization.

17 WIND ENERGY↗

DOE OSTI2020

Wake steering optimization under uncertainty

Turbines in wind power plants experience significant power losses when wakes from upstream turbines affect the energy production of downstream turbines. A promising plant-level control strategy to reduce these losses is wake steering, where upstream turbines are yawed to direct wakes away from downstream turbines. However, there are significant uncertainties in many aspects of the wake steering problem. For example, infield sensors do not give perfect information, and inflow to the plant is complex and difficult to forecast with available information, even over short time periods. Here, we formulate and solve an optimization under uncertainty (OUU) problem for determining optimal plant-level wake steering strategies in the presence of independent uncertainties in the direction, speed, turbulence intensity, and shear of the incoming wind, as well as in turbine yaw positions. The OUU wake steering strategy is first examined for a two-turbine test case to explore the impacts of different types of inflow uncertainties, and it is then demonstrated for a more realistic 11-turbine wind power plant. Of the sources of uncertainty considered, we find that wake steering strategies are most sensitive to uncertainties in the wind speed and direction. When maximizing expected power production, the OUU strategy also tends to favor smaller yaw angles, which have been shown in previous work to reduce turbine loading. Ultimately, the plant-level wake steering strategy formulated using an OUU approach yields 0.48?% more expected annual energy production for the 11-turbine wind plant than a strategy that neglects uncertainty when considering stochastic inputs. Thus, not only does the present OUU strategy produce more power in realistic conditions, but it also reduces risk by prescribing strategies that call for less extreme yaw angles.

17 WIND ENERGY↗

DOE OSTI2021

Golden Eagle Behavioral Modeling Enabled by High-Fidelity Atmospheric Models

The DOE-funded Golden Eagle Behavioral Modeling project combines knowledge of eagle behavior, eagle telemetry data, high-fidelity atmospheric and wind power plant flow models, and machine learning to develop tools that predict behavior and risk around wind power plants. This presentation provides background on the project and modeling approaches, as well as recent modeling and validation results from the region around the Top of the World wind plant in Wyoming.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2023

A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]

A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. The A2E2G platform can be used as a high-level controller for a wind plant for market participation and real-time wind plant control. The A2E2g platform is a holistic Python tool with modules that can be run to 1) advise on market participation and 2) control and operate a wind power plant in real time. The A2E2g framework assumes two stages: the first stage is in day-ahead and the second stage is in real-time. Managing uncertainty is key in the first stage and managing variability is key in the second stage. The different components have models written and developed in the Python programming language. The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).

Sinner, Michael↗

DOE OSTI2025

Editorial for the Collection "Preparatory Work for the American Wake Experiment (AWAKEN)"

The American WAKE experimeNt (AWAKEN) is a large field campaign focused on gathering observations for improved understanding of atmospheric and wind power plant flow physics, one of the outstanding needs for the wind energy community as described in the Science paper by Veers et al.1 "Grand challenges in wind energy." AWAKEN was planned over several years with an international consortium of numerous stakeholders, including national laboratories, academic researchers, wind turbine manufacturers, and wind farm operators. A highlight of the AWAKEN campaign is the extensive use of remote sensing instrumentation to characterize the atmosphere and its interactions with wind power plants, enabled by recent developments in lidar, radar, and thermodynamic profiling technology. Advanced modeling techniques like mesoscale and large-eddy simulations (LES) also played an important role in the preparation of the experiment and the interpretation of the experimental data collected. This special-topic issue for the Journal of Renewable and Sustainable Energy presents a collection of 12 papers that describe the preparatory work and some initial analyses from the AWAKEN campaign. An overview of the contents of the various papers in this special issue is provided in Sec. II.

17 WIND ENERGY↗

NASA NTRS1975

Wind energy utilization: A bibliography

Bibliography cites documents published to and including 1974 with abstracts and references, and is indexed by topic, author, organization, title, and keywords. Topics include: Wind Energy Potential and Economic Feasibility, Utilization, Wind Power Plants and Generators, Wind Machines, Wind Data and Properties, Energy Storage, and related topics.

Source record↗

DOE OSTI2020

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗

DOE OSTI2022

Wind and Solar Hybrid Power Plants for Energy Resilience

Wind-solar-storage hybrid power plants represent a significant and growing share of new proposed projects in the United States (U.S.). Their uptake is supported by increasing renewable energy market share, technical abilities for dispatch and control, and decreasing wind, solar, and battery storage costs. Simultaneously, generation and storage resources are increasingly used in distributed power systems. While concerns around the reliability of the aging, transforming U.S. electric grid are growing, diversifying energy resources through hybridization or spatial distribution provides an opportunity to enhance power system resilience compared to single-source generation. Understanding where to build hybrids for resilience value, rather than bulk power supply, has not been fully explored in previous studies. Therefore, in this study, we complete a national complementarity analysis to identify areas in the U.S. that are particularly suited for wind-solar hybrid power plant development. We show the importance of seasonal and diurnal patterns in assessing complementarity, and identify that regions in the Great Plains, Midwest, and Southeast are particularly suited for hybrid power plants. We demonstrate the resilience value of hybridization for a reference system based near Memphis, Tennessee, and show optimal sizing of wind, solar, and storage assets given 1.0 and 0.9 critical load factors. Results indicate that pairing wind and solar assets better meet constant load demand and reduce storage requirements compared to solar alone. These results enable future work integrating complementarity metrics in resilience frameworks and indicate a need for more finer resolution of local resource, demand, and hazard data.

14 SOLAR ENERGY↗

DOE OSTI2023

On the Low Risk of Subsynchronous Resonance (SSR) in Type III Wind Turbines Operating in Grid-Forming Control

grid-following turbine↗

DOE OSTI2023

On the Low Risk of SSR in Type III Wind Turbines Operating with Grid-Forming Control

We have shown in previous work that the risk of subsynchronous resonance between wind power plants with Type III wind turbines and series-compensated transmission lines is low when the wind turbines are operated in grid-forming (GFM) mode instead of the standard grid-following mode. This paper explains the fundamental mechanism behind the improved damping characteristics by modeling the positive- and negative-sequence impedances of Type III wind turbines in GFM control mode. Here it is discovered that the GFM control naturally acts against the negative resistance behavior of Type III wind turbines at subsynchronous frequencies that results from an interaction between the rotor-side converter current controller and negative slip. The developed impedance models in the sequence domain and the improved damping behavior are verified using PSCAD simulations of a 2.5-MW Type III GFM wind turbine. The modeling predictions are also supported by experimentally measuring the impedance response of a 2.5-MW Type III wind turbine in GFM mode.

17 WIND ENERGY↗

DOE OSTI2022

Optimizing the physical design and layout of a resilient wind, solar, and storage hybrid power plant

We report as wind and solar technologies improve and their costs decrease, the share of power produced by these sources will increase. As the market penetration increases, these power sources will need to provide grid services, such as dispatchability, in addition to providing energy. One way to reduce variability, provide higher quality power to the grid, and address local grid stability issues is through colocating wind and solar power plants. In addition to operating reliably during normal operating conditions, in scenarios with high penetrations of renewable generation, it is important that these hybrid plants can withstand production disruptions and continue to supply power despite prolonged resource reduction, extreme weather events, or other disruptions. In this paper, we present a methodology to optimize a wind-solar-battery hybrid power plant down to the component level that is resilient against production disruptions and that can continually produce some minimum required power. We introduce the models and assumptions we used to simulate a hybrid power plant as well as the design variable parameterization and specific methods we used to optimize the plant. We demonstrate the performance of our method by comparing a plant optimized for different objectives, generation outage durations, minimum power requirements, and power purchase agreements. Although the plant design is sensitive to model parameters and various other assumptions, our results demonstrate some of the optimal designs that occur in different scenarios and what one should expect when designing a hybrid wind-solar-storage power plant.

14 SOLAR ENERGY↗