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At least 289 records · Page 16

Develop Wake Mitigation Strategy (CRADA CRD-17-00693 Final Report)

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. In an autonomous wind farm, enabling cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving an autonomous wind farm is to develop algorithms that provide necessary information to ensure reliable, robust, and efficient operation of wind turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. In this work consensus control is applied in a hybrid analysis to data from an existing wind farm to demonstrate the benefit of consensus control.

17 WIND ENERGY↗

Autonomous Aerial Power Plant Inspection in GPS-denied Environments

Inspection of coal-fired power plants is frequently dangerous, includes difficult places to reach, and can turn expensive due to the downtimes and cost of inspection crew. Robotic systems have shown capabilities to address some of these issues, but most of the current robotic inspection technology in power plants is designed for specific components. Conversely, recent advances in machine vision have empowered aerial platforms for long-range, remotely-controlled, GPS-based inspections of industrial plants. This capability has led to wide spread utilization of aerial robots (commonly termed Drones, UVS or UAS) platforms for inspection in less challenging environments where both collision avoidance, and GPS reception are not significant issues. The challenge in adapting airborne technology for power plant inspection lies in internal structures and the complex network of piping, and distribution systems, which impose significant risks for collision and can hinder the reception and transmission of GPS signals. The current state of the art in aerial inspection technology within the energy sector is controlled via radio control, and utilizes GPS-based navigation, for inspection of large-scale plants such as offshore platforms and wind turbine parks. Nevertheless, close-range and autonomous inspection in the GPS-denied environments of power plants has not yet been achieved, as it requires precise guidance and navigation with real-time situational awareness and obstacle avoidance capabilities. This endeavor introduced the use of rotary wing flying robots, due to their station keeping and vertical take-off capabilities for power plant components inspection. To enable close quarter inspection two methods were used. One method uses the 3D CAD (Three-dimensional Computer-Aided Design) model of the asset to inspect to generate the UAV’s inspection path. To acquire, analyze and process the 3D model, first, the STL file is produced to obtain surface points and vectors normal to the surface. Later, by introducing other variables such as wall offset and a controlled trajectory between each outline and each subsequent layer, the flight path is generated. The proposed framework will generate a path that will pass as close as desired from the surface and navigate in intricate environments. A second method, use advanced manufacturing techniques such as CNC (Computer Numerical Control) and additive manufacturing. Once the inspection flight path is obtained, vision-based navigation systems are employed to have the UAV autonomously tracking the provided trajectory. Finally, Artificial Intelligence-enabled developments are in charge of detecting cracks and corrosion in structural components of power plants. The proposed methods are validated in simulations, laboratory and industrial setups, where it is shown that the developed systems acting together enable close-quarter autonomous aerial inspection and mapping in power plant assets. The system can be further improved by adding more sensors to navigate in different GPS-denied environments, with non-homogeneous lighting conditions, dust and in general situations where vision-based systems may fail.

01 COAL, LIGNITE, AND PEAT↗

Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models

Due to the interaction between the wake of an upstream turbine on a downstream turbine, power losses and increased fatigue loads occur. By yawing the upstream turbine with regard to the wind direction, one can potentially reduce the power losses of the downstream turbine and reduce the fatigue loads. The evolution of the wake depends on the pressure gradient within the near-wake region and the turbulent kinetic energy and must be incorporated in existing wake steering algorithms to provide an accurate estimation of the wake flow. This paper will show a first approach to implement a near-wake model and a turbulence model in the curled wake model within the controls-oriented framework FLORIS. The near-wake model is based on an analytical expression of the velocity profile to model the pressure gradient. Furthermore, two turbulence models are incorporated within the curled wake model based on a Gaussian-distribution and a mixing length formulation. The adapted curled wake model is then assessed with the measurement data acquired in the wind tunnel at ForWind – University of Oldenburg. The evaluation of the models show good agreement for the velocity deficit and representation of the near-wake region. Furthermore, the turbulent kinetic energy behaved as expected in comparison to other work, showing a ring of high turbulent kinetic energy at non-yawed condition which is deflected to a curled shape at large yaw angles with the turbulence model based on a mixing length formulation.

FLORIS↗

SuperLab 2.0 Showcase: Connecting Five Labs to Tackle Grid Complexity and Unlock Unique Grid Asset Potential

SuperLab 2.0 (a five-lab demonstration) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, photovoltaics, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactors, control centers, and gas turbines, across five U.S. Department of Energy (DOE) national laboratories: National Laboratory of the Rockies (NLR), Idaho National Laboratory, National Energy Technology Laboratory, Lawrence Berkeley National Laboratory, and Sandia National Laboratories. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance DOE network, and are controlled via a centralized energy controller hosted at NLR's Advanced Research on Integrated Energy Systems facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling and Analysis of Wind Turbine Wake Vortex Evolution Due to Time-Constant Spatial Variations in Atmospheric Flow

Modern utility-scale wind turbines are evolving toward larger, lighter, and more flexible designs to meet the growing demand for renewable energy while minimizing logistical costs. However, these advancements in lightweight design result in heightened aeroelastic sensitivity, leading to complex interactions which affect the rotor’s capacity to withstand aerodynamic loading and the cascading effects that manifest in the wake’s vortex-structure evolution under variable atmospheric conditions. In this paper, we analyze the influence of stream-wise fluctuating atmospheric flow conditions on wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex–wake interactions for a range of conditions with spatially variant atmospheric flow. CODEF solutions for turbine operation in wind conditions featuring only one parameter fluctuation are compared to wind conditions with several wind parameter variations in combination. By isolating individual inflow variations and comparing them to multi-parameter scenarios, we determine the contributions of each atmospheric factor to rotor dynamics, wake evolution, and downstream wind farm interactions. The purpose of this paper is to analyze the effects of spatial variations in atmospheric flow on the topological evolution of wind turbine vortex wakes, which constitutes a gap in the current understanding of wind turbine wake dynamics. The insights gained from this study are particularly valuable for the development of wind farm control strategies aimed at mitigating the adverse effects of wake interactions, enhancing energy capture, and improving the overall stability of wind farm operations. With these insights, we aim to contribute to the development of modeling and simulation tools to optimize utility-scale wind power plants operating in diverse atmospheric environments.

Farrell, Alayna (ORCID:000000023555720X)↗

Leveraging generative artificial intelligence to bridge domain gaps in wind turbine research

A central challenge in wind turbine health monitoring is the scarcity of real-world data due to limited instrumentation, leading researchers to rely on simulation models that often suffer from reduced fidelity. However, even within simulation environments, discrepancies arise because of modeling assumptions, and configuration fidelities, creating domain gaps that limit the transferability of learned representations. Here, to investigate domain translation under controlled conditions, this project explores the use of generative artificial intelligence, specifically cycle-consistent generative adversarial networks (CGANs), to bridge the gap between OpenFAST simulation models representing 1.5 MW and 5 MW wind turbines. A physics-informed CGAN architecture is introduced, where a simplified turbine tower dynamics model is incorporated into the training loss to ensure physically consistent outputs. Quantitative results showed moderate to high agreement in frequency-domain features. Incorporating the physics-informed loss function improved the R 2 values by 30%, reduced the RMSE from 1.39 to 1.1 m/s 2 , and reduced training time by 82%. Furthermore, under increased turbulence intensity (IEC Category A), the RMSE remained stable at approximately 1.1 m/s 2 . While the present study is entirely simulation-based, it establishes a pipeline for evaluating physics-informed generative domain translation, which may serve as a foundation for future simulation-to-reality validation studies.

17 WIND ENERGY↗

Optimized Carbon Fiber Composites in Wind Turbine Blade Design: Follow-On Studies

This project has identified opportunities to bring further reductions in the mass and cost of modern wind turbine blades through the use of alternative material systems and manufacturing processes. The fiber reinforced polymer material systems currently used by the wind industry have stagnated as the technology continues to mature and as a means to reduce risk while introducing new products with continually increasing blade lengths. However, as blade lengths continue to increase, the challenge of controlling blade mass becomes even more critical to enabling the associated levelized cost of energy reductions. Stiffer and stronger reinforcement fibers can help to resolve the challenges of meeting the loading demands while limiting the increase in weight, but these materials are substantially more expensive than the traditional E-glass fiber systems. One goal of this project and associated work is to identify pathways that improve the cost-effectiveness of carbon fiber such that it is the reinforcement of choice in the primary structural elements of wind blades. The use of heavy-tow textile carbon fiber material systems has been shown to reduce the blade mass by 30-31% when used in the spar cap and by up to 7% when used in edgewise reinforcement. A pultrusion cost model was developed to enable a material cost comparison that includes an accurate estimate of the intermediate manufacturing step of pultrusion for the carbon fiber composite. Material cost reductions were revealed in most cases for the heavy-tow textile carbon fiber compared to infused fiberglass. The use of carbon fiber in the edgewise reinforcement produced the most notable material cost reduction of 33% for the heavy-tow textile carbon fiber. The mass and cost savings observed when using carbon fiber in edgewise reinforcement demonstrate a clear opportunity of this design approach. A carbon fiber conversion cost model was expanded to include a characterization of manufacturing costs when using advanced conversion processes with atmospheric plasma oxidation. This manufacturing approach was estimated to reduce the cost of carbon fiber material systems by greater than 10% and can be used with textile carbon systems or traditional carbon fiber precursors. The pultrusion cost model was also used to assess the opportunity for using pultruded fiberglass in wind blades, studying conventional E-glass fiber reinforcement. When using pultruded fiberglass as the spar cap material for two design classifications, the blade weight was reduced by 6% and 9% compared to infused fiberglass. However, due to the relatively large share of the pultrusion manufacturing cost compared to fiber cost, the spar cap material cost increased by 12% and 7%. When considering the system benefits of reduced blade mass and potentially lower blade manufacturing costs for pultruded composites, there may be opportunity for pultruded E-glass in wind blade spar caps, but further studies are needed. There is a clearer outcome for using pultruded fiberglass in the edgewise reinforcement where it resulted in a blade mass reduction of 2% and associated reinforcement material cost reduction of 1% compared to infused E-glass. The use of higher performing glass fibers, such as S-glass and H-glass systems, will produce greater mass savings but a study is needed to assess the cost implications for these more expensive systems. The most likely opportunity for these high-performance glass fibers is in the edgewise reinforcement, where the increased strength will reduce the damage accumulation of this fatigue-driven component. The blade design assessments in this project characterize the controlling material properties for the primary structural components in the flapwise and edgewise directions for modern wind blades. The observed trends with low and high wind speed turbine classifications for carbon and glass fiber reinforced polymer systems help to identify where cost reductions are needed, and where improvements in mechanical properties would help to reduce the material demands.

17 WIND ENERGY↗

Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads

Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and extreme changes in wind direction are also considered for the 5 MW model. Perhaps surprisingly, veer is identified as an important driver of main-bearing load fluctuations. Upscaling results indicate that similar behaviour holds as turbines become larger, but with mean loads and load fluctuation levels increasing at least cubically with the turbine rotor radius. Strong links between turbine control and main-bearing load response are also observed.

17 WIND ENERGY↗

Determining the Reaction Time for Triggering Supportive Control Actions to Guarantee Adequate Frequency Response in Smart Grids

The progressive integration of renewable energy resources in the modern power grid can result in unsatisfactory frequency responses. To address this problem, wind turbine generators (WTGs), in particular, can be employed to support the power grid. Most works, however, only consider a simple step disturbance. In this paper, a new class of worst-case disturbances is introduced and their nefarious impact on renewable-penetrated power systems is investigated. The worst-case disturbances are derived using optimal control theory. More importantly, the proposed mechanism allows to determine the reaction time to trigger supportive control actions of WTGs to ensure satisfactory frequency response. Numerical results are provided and the effects of the worst-case disturbance on the reaction time are presented.

Luo, Jiecai↗

Coupled Aerodynamic and Hydrodynamic Hybrid Simulation of Floating Offshore Wind Turbines

The development and innovation of floating offshore wind energy in the U.S. requires detailed high-fidelity observations and measurements of turbine and platform loading due to wind, waves, and currents. However, full-scale and quasi-full-scale experiments require significant financial and temporal investments for construction, experimental testing, and long-term field campaigns. To support the commercial advancement of the offshore wind energy industry, specialized wind tunnel and wave basin experimental facilities are critical to be able to test FOWT designs at small scale under controlled conditions prior to full-scale deployment. Oregon State University (OSU) is internationally known as a leader in water and energy research, development, and testing. The O.H. Hinsdale Wave Research Laboratory (HWRL) and the Wallace Energy Systems and Renewables Facility (WESRF) at OSU have extensive experience building, modeling, monitoring, controlling, and actuating scaled systems. Experiments on wave-structure interaction have been performed at the HWRL since its establishment in 1972. Studies have included the interaction of waves with coastal structures (breakwaters, seawalls, buildings, cylinders, bridges, fixed foundations of offshore wind turbines, etc.) and with floating structures (e.g., wave energy converters, maneuvering of vessels, etc.). Hinsdale is actively used by marine energy technology developers, both for private testing and OSU-collaborative research projects. However, despite the availability of several large-scale facilities for hydrodynamic testing (at OSU and elsewhere in the U.S.), existing experimental laboratories are generally limited in their ability to accurately generate combined wind and wave conditions. The simulation of both wind and waves in experimental testing is complicated due to a number of constraints, including: [i] incompatible similitude laws governing the wind and waves for scaled experiments, [ii] producing accurate wind over a large enough control volume via fans, and [iii] generating wind that reasonably represents the atmospheric boundary layer in existing wave basins/flumes. Hence, physical test data providing insight into the simultaneous wave- and wind-structure response of floating offshore wind components can be difficult to generate. Given the aforementioned challenges in classic hydrodynamic experiments, the motivation of this project is to establish a real-time hybrid simulation (RTHS) approach that can apply aero- and hydro-dynamic loading by augmenting wave-only experimental facilities with virtual aerodynamic forces through numerical models representing the remaining dynamic forces. RTHS is a physical-numerical approach that partitions a prototype system into physical and numerical sub-assemblies that interact with each other through actuators and sensors in real time. In coupling physical and numerical models, the hybrid simulation approach applied herein is ideal for problems with: (1) structures subjected to different scaling laws, such as floating offshore wind turbines subjected to combined aero/hydro-dynamic loading, (2) structures that are too large or complex to be tested entirely in a laboratory setting, such as deep-water mooring applications, and (3) component testing, where the behavior of a portion of the assembly is uncertain but still interacts with other portions of the structure, such as testing the fatigue life of turbine blades. Few U.S. experimental facilities are able to test simultaneous aero- and hydro-dynamic loading and none can accurately produce aero/hydro-dynamic response on scaled FOWT models due to conflicting similitude laws between the wind (commonly Reynolds) and the waves (commonly Froude). To aid in accelerating the development of the U.S. floating offshore industry, there is a significant need to develop a flexible, modular framework that can expand the capacities of existing wave-only laboratories. The project goal is to demonstrate a hydrodynamic real-time hybrid simulation (hydro-RTHS) framework that couples numerical wind and physical waves acting on a FOWT, thus representing simultaneous aero/hydro-dynamic loading. The FOWT is partitioned into a full-scale numerical sub-assembly associated with the aerodynamics and a model-scale physical sub-assembly associated with the hydrodynamics. The numerical-physical partition associated with hydro-RTHS mitigates scaling constraints by supplying different scaling laws to the physical and numerical sub-assemblies. Herein, length, force, and time are scaled and exchanged between the sub-assemblies using Froude scaling to represent the open-channel flow in the physical sub-assembly. Other similitude laws could also be utilized depending on the problem definition. It is envisioned that the ability to model FOWTs under waves and wind, with mitigation of similitude distortions, would result in reduced development costs (currently, FOWT concept development is performed with full-size pro- totypes at enormous expense and risk) and increase the reliability of the FOWT industry (since extreme wave and wind conditions and contingency events can be tested safely in a controlled environment).

16 TIDAL AND WAVE POWER↗

Do ambient shear and thermal stratification impact wind turbine tip-vortex breakdown?

Modern wind turbines experience uneven inflow conditions across the rotor, due to the ambient flow’s shear and thermal stratification. Such conditions alter the shape and length of turbine wakes and thus impact the loads and power generation of downstream turbines. To this end, understanding the spatial evolution of the individual wakes under different atmospheric conditions is key to controlling and optimising turbine arrays. With this numerical study we aim to obtain a better understanding of the fundamental physics governing the near-wake dynamics of wind turbines under shear and thermal stability, by examining their tip-vortex breakup mechanisms. Our approach considers scale-resolving simulations of a single turbine wake under a linear shear profile as well as the application of harmonic tip perturbations to trigger flow instabilities. For the subsequent analysis we use the proper orthogonal decomposition (POD) method to extract coherent structures from the flow, and we also calculate mean kinetic energy fluxes to quantify each coherent structure’s contribution to wake recovery. The wake’s helical spiral is found to hinder wake recovery for all studied ambient flow conditions, whereas the mutual inductance instability has positive MKE flux leading to an enhanced wake recovery. Finally, the ambient shear has the largest impact on the local MKE flux with respect to downstream location by changing the shape of the curve and location of extrema, whereas thermal stratification has only a minimal impact on the magnitude of the near-wake local MKE flux distribution.

17 WIND ENERGY↗

Spectral proper orthogonal decomposition of active wake mixing dynamics in a stable atmospheric boundary layer

Recent advancements in the use of active wake mixing (AWM) to reduce wake effects on downstream turbines open new avenues for increasing power generation in wind farms. However, a better understanding of the fluid dynamics underlying AWM is still needed to make wake mixing a reliable strategy for wind farm flow control. In this work, a spectral proper orthogonal decomposition (SPOD) is used to analyze the dynamics of coherent flow structures that are induced in the wake through blade pitch actuation. The data are generated using the ExaWind software suite to perform large eddy simulations of an NREL 2.8 MW turbine operating in a stable atmospheric boundary layer. SPOD tracks the modal behavior of flow structures from their generation in the turbine induction field through their growth in the near-wake region and to their subsequent evolution and energy transfers in the far wake. SPOD is shown to be a useful tool in the context of AWM because it translates the wavenumber and frequency inputs to the turbine controller to structures in the wake. A decomposition of the radial shear stress flux in the wake is also developed using SPOD to measure the contribution of coherent flow structures to mean flow turbulent entrainment and wake recovery. The effectiveness of AWM is connected to its ability to excite inherent structures in the wake of the turbine that arise using baseline controls. The effects of AWM on blade loading are also analyzed by connecting the axial force along the blade to the SPOD analysis of the turbine induction field. Lastly, the performance of different AWM strategies is demonstrated in a two-turbine array.

17 WIND ENERGY↗

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↗

American WAKE Experiment (AWAKEN) Field Campaign Report

The American WAKE experimeNt (AWAKEN) was a large-scale, international collaborative field campaign funded primarily by the U.S. Department of Energy (DOE) Wind Energy Technologies Office. Its main purpose was to gather detailed observations of wind farm-atmosphere interactions to improve understanding of wind farm physics, validate and improve simulation tools, lower uncertainties in wind farm modeling, understand environmental impacts, and ultimately reduce the cost and increase the reliability of wind energy systems. The campaign specifically focused on seven testable hypotheses that include characterizing wind turbine and wind farm wake effects, wind farm blockage, turbulent mixing, structural loading impacts, local environmental impacts, and testing wind farm control technologies. AWAKEN was a highly collaborative effort involving numerous agencies, including: DOE, through the Wind Energy Technologies Office and the Office of Science Atmospheric Radiation Measurement (ARM) User Facility, the U.S. Department of Commerce through the National Oceanic and Atmospheric Administration, many American universities, and internationally funded collaborators from Germany and Brazil.

17 WIND ENERGY↗

SuperLab 2.0 Showcase: Connecting Five Labs to Tackle Grid Complexity and Unlock Unique Grid Asset Potential

SuperLab 2.0 (5-Lab Demo) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, PV, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactor (SMR), control centers, and gas turbines, across five DOE national laboratories-NLR, INL, NETL, LBNL, and SNL. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance U.S. Department of Energy's (DOE) network, and controlled via a centralized energy controller hosted at NLR's ARIES facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility. SuperLab 2.0 (5-Lab Demo) showcased a major advancement in federated national laboratory collaboration, enabling real-time, cross-laboratory experimentation to coordinate geographically dispersed distributed energy resources (DERs) using various communication protocols and networks. SuperLab 2.0 (5-Lab Demo) built on previous demonstrations conducted between NLR-PNNL and NLR-INL connecting diverse assets including distant protection devices, a SMR simulator, and a high temperature electrolyzer (HTE). Previous demos were based on a single connection between two labs with minimal coordination challenges. The 5-Lab demo with a centralized controller, distributed testbeds across different geographical locations, and use of protocols-based communication represents a scenario closer to real-world grid operations that coordinate resources across a region to meet system needs. This experiment studied how local DER controllers interact with a centralized energy controller during normal and abnormal events to maintain reliability. The SuperLab team across the five labs implemented a notional power system model equivalent of transmission and distribution lines, represented by the data networks interconnecting the labs. Each lab continuously exchanged local parameters (such as P and Q) from its Hardware-In-Loop (CHIL) and Power Hardware-In-Loop (PHIL) assets through centralized energy controller at NLR, enabling real-time interaction and coordination across sites. By leveraging ESnet as the communication backbone, the team successfully operated the distributed assets as a unified power system, with each bus represented by a different laboratory. This setup mirrors how assets interact in real-world power systems across dispersed locations with various protocols and latencies. At each lab site, assets were operated using their own local controllers which were coordinated through an overarching operation and control layer of centralized energy controller, equivalent to how an energy management system (EMS) orchestrates assets across a regional or national grid. SuperLab's federated connectivity utilized a Digital Real-Time Simulators (DRTS)-type gateway to connect Controller Hardware-In-Loop (CHIL) and PHIL assets between labs. To enable this federated connection through ESnet, a deterministic network was established where latency variations were consistent. This consistency allowed the development of digital filters for the power system assets across CHIL and PHIL interfaces to avoid unstable and unreliable grid conditions. This report provides an overview of the cross-laboratory configuration and offers insights into interconnecting geographically distributed research assets to test them as if they were co-located. This experiment represents a step toward linking nine DOE national laboratories, enabling nation-wide simulations that can address utility-driven challenges with grid resilience, flexibility, and modernization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reconfigurable Real-Time Power Grid Emulator for Systems With High Penetration of Renewables

Novel power system control and new utility devices need to be tested before their actual deployment to the power grid. To assist with such a testing need, real-time digital emulators such as RTDS and Opal-RT can be used to connect to the physical world and form a hardware in the loop (HIL) emulation. However, due to the limitations of today's computational resources, the accuracy and fidelity suffer from different levels of model reductions in purely digital simulations. CURENT has developed a reconfigurable electric grid hardware testbed (HTB) to overcome the limitations of digital emulators. The HTB has been used to develop measurement, control, modeling, and actuation techniques for a national grid with a high penetration of renewables. The power electronic-based system includes emulators for synchronous generators; photovoltaics with grid-interfacing inverter; wind turbines; induction motor loads, ZIP loads, power electronic loads; batteries; ac and dc transmission lines; short circuit faults and grid relay protection; and a multiterminal HVDC overlay including power electronics interfaces. The system contains real elements of power flow, measurement, communication, protection, and control that mimic what would be seen in an actual electric grid. This paper presents an overview of the HTB and several scenarios that have been run to determine control and actions needed for the future power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

50 MW Segmented Ultralight Morphing Rotors for Wind Energy

A multi-institutional team designed a 50 Megawatt (MW) rated wind turbine featuring downwind aeroelastic morphing to reduce blade loads and allow an ultralight segmented rotor (mass reduction of about 25% compared to a conventional upwind rotor). The team used a control co-design approach with state-of-the art simulations including for the rotor and tower design using non-linear fluid-structure interactions and control algorithms, and the team also designed, built, and field-tested an aeroelastically-scaled downwind rotor to demonstrate this novel technology and validate the design tool fidelity. In a follow-on phase, these results were used along with an updated Levelized Cost Of Energy (LCOE) methodology to co-design a more detailed set of 25 MW rated turbine designs (including individual pitch control) based on minimum LCOE with highly flexible blades for an Atlantic Ocean offshore fixed-bottom design targeted towards market technology evaluation. A set of upwind and downwind designs at 25 MW rated scales were found to provide the best LCOE, with strong improvements over all previous offshore reference turbines (NREL 5MW, DTU 10 MW and IEA 15 MW). The optimized design would represent the world’s largest offshore turbine design, which combines several state-of-the-art structural, aerodynamic, and control technologies into a new and optimized system concept.

17 WIND ENERGY↗

Guest Editorial: Control interactions in power electronic converter dominated power systems

The modern power systems have undergone significant transformations at the generation, transmission, distribution, and utilization levels due to the remarkable advancements in power electronic converter technology. Power electronic converters are now prevalent in various applications, including wind turbine converters, photovoltaic inverters, flexible AC transmission systems (FACTS) and high-voltage DC (HVDC) converters, distributed generators, microgrids, and electric vehicles. The widespread adoption of power electronic converters has revolutionized the power system by providing fast and flexible controllability. However, their unique characteristics, such as fast response, multi-time scale dynamics, reconfigurable control, and varying sizes and capacities, have introduced new stability challenges, fundamentally altering the dynamics of modern power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗