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DOE OSTI2023

Joint Resource Modeling and Assessment for Hybrid Distributed Solar and Wind Systems

The inherent variability and uncertainty in distributed energy resources can presents myriad challenges to the planning and operations of power systems. These risks are poised to become larger as the penetration of renewable energy sources rises in the power generation mix. Hybrid solar-wind energy systems are able to mitigate some of these risks by their complementary resource availability. Surface solar and wind fields are coupled and correlated in both space and time. Appropriately estimating the hybrid solar wind energy system requires simulating the spatio-temporal structure of these fields that can be produced for each time horizon. We introduce a novel joint spatio-temporal stochastic differential equation (SPDE) approach that captures the spatio-temporal dynamics of solar and wind fields and their joint dependency over a domain for each time step. In the case study on Colorado, we consider nonstationary three-level hierarchical spatio temporal models for both hourly solar irradiance data and wind speed data in Colorado. Dependence between the solar irradiance data and wind speed data is captured by a shared spatio-temporal random effect. Our approach performs well in terms of the prediction score criterion.

joint modeling↗

DOE OSTI2018

Probabilistic Wind Power Ramp Forecasting Based on a Scenario Generation Method

Wind power ramps (WPRs) are particularly important in the management and dispatch of wind power and currently drawing the attention of balancing authorities. With the aim to reduce the impact of WPRs for power system operations, this paper develops a probabilistic ramp forecasting method based on a large number of simulated scenarios. An ensemble machine learning technique is first adopted to forecast the basic wind power forecasting scenario and calculate the historical forecasting errors. A continuous Gaussian mixture model (GMM) is used to fit the probability distribution function (PDF) of forecasting errors. The cumulative distribution function (CDF) is analytically deduced. The inverse transform method based on Monte Carlo sampling and the CDF is used to generate a massive number of forecasting error scenarios. An optimized swinging door algorithm is adopted to extract all the WPRs from the complete set of wind power forecasting scenarios. The probabilistic forecasting results of ramp duration and start-time are generated based on all scenarios. Numerical simulations on publicly available wind power data show that within a predefined tolerance level, the developed probabilistic wind power ramp forecasting method is able to predict WPRs with a high level of sharpness and accuracy.

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DOE OSTI2021

Remote Monitoring and Diagnostics of Pitch-Bearing Defects in an MW-Scale Wind Turbine Using Pitch Symmetrical-Component Analysis

Recently, multiple wind turbine failure databases have reviewed that the pitch system is one of the subassemblies with the highest failure rates and largest contributors to the overall downtime. Therefore, there has been an increasing interest to provide remote health monitoring for wind turbine pitch system. While most of the research articles are discussing pitch actuation system (hydraulic or electric actuator) faults only, there is very limited research on pitch-bearing-defect detection. This article provides a remote and hardware-free solution to monitor multiaxis pitch-bearing health condition called pitch symmetrical-component analysis. It leverages readily available low-resolution (100 Hz) electrical measurements, mechanical measurements, and control signals from the existing pitch control platform, and innovatively applies symmetrical-component analysis in multiphase ac system to multiaxis pitch control system and introduces multiaxis pitch-bearing degradation trending curves. This hardware-free solution can be directly applied to the existing wind turbines and successfully give the wind farm operator an early warning before multiaxis pitch bearing fails. It has been proved to be accurate, low cost, and has minimum impacts on turbine normal operation, and has been validated by field data from several North America MW-scale wind farms. This approach turns out to be the first hardware-free (no additional hardware needed) method to remotely monitor and diagnose multiaxis wind turbine pitch-bearing condition.

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DOE OSTI2016

Managing Wind Power Uncertainty Through Strategic Reserve Purchasing

With the rapidly increasing penetration of wind power, wind producers are becoming increasingly responsible for the deviation of the wind power output from the forecast. Such uncertainty results in revenue losses to the wind power producers (WPPs) due to penalties in ex-post imbalance settlements. This paper explores the opportunities available for WPPs if they can purchase or schedule some reserves to offset part of their deviation rather than being fully penalized in the real time market. The revenue for WPPs under such mechanism is modeled. The optimal strategy for managing the uncertainty of wind power by purchasing reserves to maximize the WPP's revenue is analytically derived with rigorous optimality conditions. The amount of energy and reserves that should be bid in the market are explicitly quantified by the probabilistic forecast and the prices of the energy and reserves. A case study using the price data from ERCOT and wind power data from NREL is performed to verify the effectiveness of the derived optimal bidding strategy and the benefits of reserve purchasing. Additionally, the proposed bidding strategy can also reduce the risk of variations on WPP's revenue.

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DOE OSTI2018

A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

Efficient management of wind ramping characteristics can significantly reduce wind integration costs for balancing authorities. By considering the stochastic dependence of wind power ramp (WPR) features, this paper develops a conditional probabilistic wind power ramp forecast (cp-WPRF) model based on Copula theory. The WPRs dataset is constructed by extracting ramps from a large dataset of historical wind power. Each WPR feature (e.g., rate, magnitude, duration, and start-time) is separately forecasted by considering the coupling effects among different ramp features. To accurately model the marginal distributions with a copula, a Gaussian mixture model (GMM) is adopted to characterize the WPR uncertainty and features. The Canonical Maximum Likelihood (CML) method is used to estimate parameters of the multivariable copula. The optimal copula model is chosen based on the Bayesian information criterion (BIC) from each copula family. Finally, the best conditions based cp-WPRF model is determined by predictive interval (PI) based evaluation metrics. Numerical simulations on publicly available wind power data show that the developed copula-based cp-WPRF model can predict WPRs with a high level of reliability and sharpness.

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DOE OSTI2019

The Second Wind Forecast Improvement Project (WFIP2): Observational Field Campaign

The science of wind energy forecasting has taken a leap forward with the unique meteorological observations gathered in complex terrain during the Second Wind Forecast Improvement Project (WFIP2). The Second Wind Forecast Improvement Project (WFIP2) is a U.S. Department of Energy (DOE) and National Oceanic and Atmospheric Administration (NOAA) funded program, with private-sector and university partners, which aims to improve the accuracy of numerical weather prediction (NWP) model forecasts of wind speed in complex terrain for wind energy applications. A core component of WFIP2 was an 18-month field campaign which took place in the U.S. Pacific Northwest between October 2015 and March 2017. A large suite of instrumentation was deployed in a series of telescoping arrays, ranging from 500 km across to a densely instrumented 2 x 2 km area similar in size to a high-resolution NWP model grid cell. Observations from these instruments are being used to improve our understanding of the meteorological phenomena that affect wind energy production in complex terrain, and to evaluate and improve model physical parameterization schemes. We present several brief case studies using these observations to describe phenomena that are routinely difficult to forecast, including wintertime cold pools, diurnally driven gap flows, and mountain waves/wakes. Observing system and data product improvements developed during WFIP2 are also described.

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DOE OSTI2019

Improving Wind Energy Forecasting through Numerical Weather Prediction Model Development

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.

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DOE OSTI2016

Comparison of Standards and Technical Requirements of Grid-Connected Wind Power Plants in China and the United States

The rapid deployment of wind power has made grid integration and operational issues focal points in industry discussions and research. Compliance with grid connection standards for wind power plants (WPPs) is crucial to ensuring the reliable and stable operation of the electric power grid. This report compares the standards for grid-connected WPPs in China to those in the United States to facilitate further improvements in wind power standards and enhance the development of wind power equipment. Detailed analyses of power quality, low-voltage ride-through capability, active power control, reactive power control, voltage control, and wind power forecasting are provided to enhance the understanding of grid codes in the two largest markets of wind power. This study compares WPP interconnection standards and technical requirements in China to those in the United States.

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DOE OSTI2020

Bat Impact Minimization Technology: An Improved Bat Deterrent for the Full Swept Rotor Area of Any Wind Turbine

The growth in the number of wind turbine generators has led to a significant number of fatal interactions with bat species. The need to reduce the number of bat fatalities while minimizing power losses is the greatest conservation challenge for wind energy development in parts of the country, according to the American Wind Wildlife Institute. Technological solutions that can also allow turbines to operate normally would generate the maximum electricity and avoid financial losses. Bats use echolocation to perceive their surroundings by listening to features of echoes from their high frequency vocal signals reflecting from targets. In this project, Frontier Wind built on previous research demonstrating that ultrasonic noise can mask echolocation and act as a repellent or deterrent to bat flight activity. Whereas the initial study only broadcast ultrasonic transmissions from the center of the turbine, the Strike Free™ system developed for this project extended the ultrasonic coverage to the entire area swept by the turbine blades. Frontier Wind designed the system components and their integration and then tested them in the lab and in the field at Pattern Energy’s Hatchet Ridge Wind Facility near Redding, California. The researchers used an acoustic model to determine the optimal configuration of transmitters along the blades to provide sound transmission coverage across the turbine rotor swept area volume. The custom ultrasonic transmitters were designed specifically for the echolocation frequencies of the four main bat species that have been shown to have died at Hatchet Ridge, although the transmitters can be customized for different frequencies as needed in other geographic locations. The Strike Free™ system shows promise for reducing bat fatalities, and the path to commercialization requires further testing to validate and optimize performance in the field.

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DOE OSTI2020

Offshore Wind Electrical Safety Standards Harmonization (Workshop Proceedings)

Offshore wind (OSW) development activity is accelerating in the United States, with over 10 gigawatts (GW) of capacity likely to be installed on the Atlantic coast before 2030. In addition, states have committed to procure over 29 GW of offshore wind. Experienced European offshore wind energy developers are beginning to make large investments into offshore wind projects in American waters, and some U.S. developers have submitted key design documents for regulatory review. European offshore wind developers possess extensive experience in other geographic markets, which greatly increases confidence that the U.S. offshore wind industry will be successful. Nonetheless, existing U.S. electrical standards and European electrical standards are significantly different. If not addressed, these differences could potentially impact worker safety.

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DOE OSTI2022

The Determinants of Offshore Wind's Role in a Future U.S. Energy System: A Preliminary Modeling Sensitivity Analysis [Slides]

Offshore wind is an emerging industry in the with rapidly changing technology advancements and an accelerating global deployment. Policy demands and interest in the United States has grown, but the long-term future for offshore wind remains uncertain. This study is designed to evaluate offshore wind's potential role in the future U.S. energy system. The analysis uses long-term power system models to assess a wide-range of power system possibilities. Specific objectives of the analysis are to: (1) identify the determinants of offshore wind deployment under different scenarios and (2) understand the impacts of substantial levels of offshore wind deployment on the power system. We also highlight future research needs for more robust understanding the opportunities and challenges to U.S. offshore wind development.

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DOE OSTI2022

Acoustic Travel-Time Tomography for Wind Energy

New remote sensing technologies for direct observation of the atmospheric flow in the proximity of operating wind turbines are necessary for the advancement of wind turbine design, wind plant control, and the validation of high-fidelity numerical models; fundamental goals of the DOE Wind Energy Technology Office's (WETO's) A2e program. Modern remote sensing technologies for commercial and research applications rely on the backscatter of light or sound waves, which limits spatial and temporal resolution and cannot produce reliable flow estimates near solid bodies or reflective surfaces. Acoustic tomography (AT) is an innovative sensing technology based on fundamental thermodynamic properties of the atmosphere and an inverse algorithm that can reconstruct both velocity and temperature fields within a network of acoustic transducers. AT relies on the direct travel path of acoustic signals between speakers and microphones in the network and can achieve much higher resolutions than conventional backscatter technologies. For wind energy R&D applications, AT represents an extremely economical option over other remote sensing technologies, integrating mature and commonly available acoustic and signal processing hardware. This report is intended as an update on the development of the AT array on the NREL Flatirons Campus (FC) and includes a brief review of the instrumentation, the calibration of equipment, signal processing, and resulting flow field estimates. Designs for future AT systems and applications are detailed in this report, including summaries of new capabilities, engineering and theoretical challenges, and anticipated costs help to outline future directions for AT technology R\&D. The potential for application of AT to utility-scale turbines is also discussed. Investing in the development of the proposed instrument will establish AT as a transformational RS technique that represents a significant advance in measurement instrumentation, enabling new fundamental insights into the structure of the atmospheric boundary layer and supporting applications for wind energy, pollution transport, and resource characterization. AT is also an extremely economical option over other RS instruments, integrating mature and commonly available acoustic and signal processing hardware.

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DOE OSTI2024

International Energy Agency 22 MW Offshore Reference Wind Turbine

The presentation will be used in a public webinar to introduce the newly developed 22 megawatt offshore reference wind turbine designed within the International Energy Agency Wind Technology Commercialization Programme Task 55 Reference Wind Turbines and Plants. The turbine was designed collaboratively by two teams at the Denmark Technical University and at the National Renewable Energy Laboratory. Reference turbines serve an important purpose in the wind energy community, since they provide openly available data for models representative of current wind turbine technology, which can be used by practitioners for a variety of modeling purposes, ranging from aerodynamic, structural, and aeroelastic turbine modeling to wind farm flow modeling, across a range of fidelities. The IEA 22 RWT aims to model machines with projected installation in the 2025-2030 time frame. The turbine has a rotor diameter of 284 meters and a hub height of 170 meters. It is a class 1-B machine with a rotor specific power nearing 350 W m-2 and it is mounted on either a fixed-bottom offshore foundation or a semi-submersible floating platform.

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DOE OSTI2025

Focal Fisheries Requirements for Floating Offshore Wind Co-Design in the Gulf of Maine and the Mid-Atlantic Bight

Floating offshore wind is an emerging renewable energy technology in U.S. waters and globally. Floating offshore wind technology is more complex than fixed-bottom installations, requiring platforms, moorings, and power cables that take up a larger footprint, both in the water column and along the seafloor. This complexity affects opportunities for compatibility between floating offshore wind and other ocean users, particularly fishermen, whose fishing gear also takes up space in the water column and along the seafloor. This report describes the results of semi-structured interviews with key fishing informants from two focal fisheries: (1) Gulf of Maine lobster (fixed gear) and (2) Mid-Atlantic Bight pelagic longline and recreational tuna (mobile gear). A total of six fishermen were interviewed: four from the Gulf of Maine and two from the Mid-Atlantic Bight. The interviews were designed to elicit information and opinions on the co-design of marine space for particular fishing gear and floating offshore wind infrastructure. Here, we provide an overview of participant fishing experience, the spatial requirements of specific gear types, self-reported comfort levels in different fishing scenarios, and concerns about accessing and operating within floating offshore wind arrays. This summary of fishermen s concerns around floating offshore wind infrastructure can guide future co-existence conversations.

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DOE OSTI2025

Floating Offshore Wind US Manufacturing and Commercialization: Cooperative Research and Development (Final Report)

NREL assessed the supply chain and workforce considerations for the OCG-Wind floater technology, a floating semi-submersible offshore wind substructure, as well sharing vessel needs to inform their installation strategy. This technical assistance was in support of the FLoating Offshore Wind ReadINess (FLOWIN) Prize Phase 2 submission. NREL provided an assessment of domestic supplier capabilities for the main components of their floating offshore wind platform design and analyzed US regional and national supply chain constraints and gaps. Thirteen interviews with companies including steel distributors, forges, foundries, ports, large component fabricators, subcomponent fabricators, and secondary suppliers provided key insights such as 1) assembly ports are the key infrastructure barrier standing in the way of unlocking the domestic assembly and component fabrication for steel-based FOW platforms, 2) domestic steel producers can supply the types and quantities of steel necessary for FOW platforms, and 3) coordination between stakeholders will be a vital part of successfully developing the supply chain and infrastructure needed to domestically produce FOW platforms. In the workforce assessment, NREL documented a step-by-step approach to conduct a place-based assessment of the foundational workforce consideration for recruiting, upskilling, and retaining a workforce, such as supportive local and state policy, nearby education and training programs, and existing relevant industry. This approach was applied to Tacoma, Washington. Tacoma was indicated to have the potential be a successful location for fabrication and assembly of floating offshore wind energy in terms of workforce development. To share data on vessel requirements to install the OCG-Wind floater, NREL compiled resources that help answer the questions related to anchor handling tug vessels, shared a database of cable laying vessels, and answered questions on complying with the Jones Act.

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DOE OSTI2025

A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Final Technical Report)

Collision of birds and bats with wind turbines is a conservation concern for both land-based and offshore wind projects. The fatality rates of birds and bats at land-based turbines are well documented. The measurement strategies on land focus on finding carcasses following collision, estimating the number of carcasses missed through searcher efficiency, carcass persistence trials and carcass fall distributions, and modeling statistically robust fatality rates. Few technologies have been developed to monitor offshore bird and bat collisions, and many that have been developed focused on detecting collisions with large birds. The few studies that have attempted to document collisions at offshore turbines do not account for smaller bodied animals or for collisions that might be missed, which prevents the calculation of statistically robust fatality rates. The overall goal of this report, A Multi-Sensor Approach for Measuring Bird and Bat Collisions with Offshore Wind Turbines (Project), was to develop an effective multi-sensor system for quantifying bird and bat collision rates, specifically for offshore wind facilities. The Project goal and resulting automated collision detection system was achieved through two major technological advancements: 1) refining The Netherlands Organisation for Applied Scientific Research’s (TNO’s) existing WT-Bird® vibration sensing system, that had successfully detected large bird collisions during daytime, to allow for improved detection of smaller birds and bats during both daytime and nighttime hours and 2) improving image processing systems and developing and integrating machine learning algorithms to automatically detect and classify small and large bird and bat collisions with offshore turbines. This final technical report (FTR) summarizes Methods , Results , Conclusions , and Lessons Learned during each of the five Tasks identified for this research and development effort. This FTR includes summaries of the following: Task 1. Initial Engineering Tests to Improve WT-Bird® Task 2. Installation of WT‐Bird® on a Utility-scale Turbine at the National Wind Technology Center – National Renewable Energy Laboratory Task 3. Field Tests and Refinement of the Object Detection System Task 4. Validation of WT-Bird® on a Land-based Turbine Task 5. Preparation for the Implementation of WT-Bird® on an Offshore Turbine. This research and development effort documented successful improvement of the WT Bird® collision detection system to detect small birds and bats, and WT-Bird® is the first collision detection system to validate results compared to land-based post-construction monitoring. The collision trials provide estimates of missed targets that can be used to estimate fatality rates, a significant improvement relative to other offshore collision monitoring systems. Advances were made in developing an edge-processing solution to reduce data storage requirements, which is important if the system is deployed for long periods of time at offshore turbines. The improved WT-Bird® system also provides an important option for wind operators on land or offshore who need to document specific details about when collisions occur, particularly efforts to further research on bat impact minimization, or when standard fatality searches are impractical (e.g. offshore) or inadequate (e.g. challenging locations on land).

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DOE OSTI2026

Wind Power as a Virtual Synchronous Generator (WindVSG)

This project investigated the theory, implemented it in hardware, and validated the Wind as a Virtual Isochronous Generator (WindVSG) concept by combining the advantages of modern dynamic inverter technologies with static, dynamic, and transient electromechanical properties of synchronous machines. During this project we demonstrated how to control the inverters of wind turbine generators (wind alone or in parallel with other GFM sources, such battery energy storage) so that wind power behaves like a synchronous machine-based power plant with a conventional prime mover. For this purpose, testing was conducted at NLR ARIES facility with real 2.5 MW wind-turbine generator operating in GFM mode under dynamic and transient conditions. The team also developed models and conducted simulations for GFM wind power to evaluate stability impacts of GFM operation on power grid. This report describes efforts by the NLR team working in collaboration GE Vernova during 3-year project.

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DOE OSTI2017

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind-Farm Design and Analysis

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevant physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.

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