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DOE OSTI2021

Powering the Blue Economy: A Survey of Station-Keeping Methods for Mooringless Platforms

The term “ocean platform” is used to reference everything from stationary, typically moored, buoys to mobile water vehicles, whether they operate on the ocean’s surface or underwater. For certain applications for which relatively stationary station-keeping conditions are desired, the use of mooring systems is not always a viable alternative either for economic, environmental, regulatory, or otherwise practical reasons, or a combination thereof, (e.g., short deployments, sensitive ecosystems, very deep project sites). Maintaining a platform at a single waypoint or reference location without being moored would require additional control systems and a power source to counteract the drift forces that would naturally displace it. Mobile platforms, which are usually untethered except for remotely operated vehicles, typically require energy input to power their station-keeping capabilities so that they hold or control their location in the ocean. Currently, most of these platforms use combustion engines or batteries for this purpose, which, depending on the specific systems, may be costly, pollute the environment, or create limitations on the length of the deployment. However, powering this kind of platforms with surrounding renewable resources (waves, currents, winds, or sun) has been identified as a promising solution to expand their application. The intent of this report is to investigate station-keeping methods for various ocean platforms that are not moored or otherwise anchored to the ocean floor, or another platform or vessel, paying particular interest to technologies that use marine renewable resources to power their operation, because that is of particular interest to the U.S. Department of Energy’s Powering the Blue Economy (PBE) initiative. As a first step, 72 articles and technical reports related to mooringless station-keeping methods were collected for review. The preliminary literature review provided a broad overview of common themes across the literature from which a descriptive methodology for analyzing various platforms was developed. That is, station-keeping methods were categorized based on their predominant energy source and consumption (renewable, nonrenewable, or hybrid if the platform uses renewable and nonrenewable resources equally), and their localization strategy (drift reduction, “path-planning or “waypoint-holding”). In addition, platform types were segregated into the following groups: buoys, surface drifters, and unoccupied surface vehicles (USVs); offshore renewable energy systems; and unoccupied underwater vehicles (UUVs). The main types of station-keeping methods encountered in this report achieve their intended localization strategy by means of drift mitigation, steering, and/or propulsion. Drift mitigation is commonly accomplished via drogues and sea anchors. Stand-along steering subsystems use control surfaces (e.g., ship rudder, wing sail, etc.) that react to ocean currents, waves, or winds to provide varying-degrees of course adjustments. Combined steering and propulsion subsystems include differential thrusters, directional thrusters separate from a primary thruster that cause the platform to pitch up/down or yaw clockwise/counterclockwise, or vectored thrusters that direct the propulsion in a range of directions relative to the platform’s local coordinate system. Propulsion is often achieved by running a motor and applying active control strategies but can also involve buoyancy shifts and using sails to generate lifting forces that propel a platform in a desired direction. Future research is primarily expected to take place in the form of a technoeconomic analysis that would aim to determine the technological viability, cost, and added value of mooringless station-keeping use cases identified through this research, including docking for UUV recharging or for georeferencing drifter buoys, deep-sea floating wind farms, U.S. Navy sonar arrays, and a Pacific Ocean wave buoy network.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Main Shaft Bending Moment Analysis for a Gamesa G97 2-MW Wind Turbine

In a collaborative project between Siemens Gamesa Renewable Energy and the National Renewable Energy Laboratory (NREL), a cost-effective method to measure dynamic main shaft torque and the influence of non-torque loads was applied to the gearbox of the Gamesa G97 2-megawatt (MW) wind turbine at the NREL Flatirons Campus and verified through a field test campaign that took place in 2023. The method involved the installation of fiber-optic sensors on the ring gear of the gearbox. Additionally, traditional strain gauges and a rotary encoder were installed on the main shaft to measure mechanical torque and orthogonal bending moments. We compare the measured total main shaft bending moments from the field test campaign to those predicted by an updated OpenFAST model of the G97 wind turbine for similar environmental conditions. We also assessed the sensitivity of the predicted bending moment to varying levels of turbulence intensity, shear exponent, and yaw error.

17 WIND ENERGY↗

DOE OSTI2025

TEAMER – Enhanced Flow Measurement for Aquantis Tidal Turbine Test

The AQ10 is a floating, two-bladed, passive yawing tidal turbine developed by Aquantis that has a 10-meterrotor diameter, 160 kW rating, and employs reliable off-the-shelf powertrain and power conversion hardware. Aquantis is planning on-water turbine power performance and loads (blade loading and thrust)testing, where the turbine will be pushed through still water up to 4 knots and placed in a ‘station keeping’ tow in a tidal race up to its rated speed. On-water testing will be conducted using vessels and floating platforms on the sea surface to improve ease of testing and reduce disturbance to the environment. In this TEAMER project, Pacific Northwest National Laboratory (PNNL) will conduct water velocity and turbulence measurements in front of the turbine during on-water testing using acoustic Doppler instrumentation. By measuring both the tidal current flowing past the turbine and the resulting electrical power output, test results will provide a power curve (power vs flow speed) for the turbine up to rated power. Measurements of turbulence and velocity shear in front of the rotor will also provide information to assess the structural response of the rotor blades. With this analysis, Aquantis can use the performance and loads data to validate Tidal Bladed and OpenFAST simulations of the measured operating conditions. Measuring the power performance of a prototype turbine is a valuable step to improving device development and conducting a complete power performance assessment to IEC/TS 62600-200 standards in the future.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Harvesting Subsea Water Motion to Provide Clean Electrical Power

This TEAMER project had three main objectives related to characterizing the performance of a vortex-induced vibration (VIV) marine energy harvesting device called the Whatever Input To Torsion (WITT). The first was to characterize the motion of the WITT device as it vibrates on top of a pipe in a natural tidal flow. The second was to measure how much electricity the WITT device generates when it is deployed on top of a pipe that is secured to the seabed with a lander. The third objective was to measure how much electricity the WITT device generates in the same configuration but with a longer pipe. This TEAMER project succeeded in satisfying the first objective by measuring the motion of the WITT device with an inertial measurement unit (IMU) mounted in the WITT housing. The motion was described by examining changes in the acceleration, pitch, roll, and yaw, and displacement. The frequency of the motion was characterized using spectral analysis. The TEAMER project succeeded in reaching the second objective by measuring the power produced by the WITT. It is reported here as the average and maximum power in hourly intervals. WITT Energy decided to not have us pursue the third objective of testing a longer pipe because the first test was unexpectedly successful at having the system vibrate at the target frequency. A longer pipe would have resulted in a decreased frequency and therefore not have been a useful test. Based on these findings, the decision was made to keep the same pipe length for both tests and improve on other aspects of the test structure that had failed during the first test. The key finding of this TEAMER project is that the WITT is capable of generating electricity in moderate flow speeds when it is in a housing that is attached to a 2.5 m pipe and secured to the seabed by a lander. This report contains the first power values for a VIV instrument that generates electricity from a pendulum swinging at the top of a long pipe. The experiment demonstrated that the vibration frequency of the device varied with the tidal current speed, which changed throughout a given tidal cycle. This meant that the desired peak frequency was not sustained for more than one hour. The success of this TEAMER test provides evidence that continued research in the area of electricity generation from VIV holds promise as a source of marine energy for offshore applications. Future tests should focus on refining the pipe length equations and improving the power take off system of the WITT power electronics. In addition, experiments aimed at expanded testing and evaluation (e.g. longer than one month) are needed to measure the power production at higher tidal current speeds and test the system's durability.

Branch, Ruth A. (ORCID:0000000202356719)↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence W - Raw Data

Sequence W: Extended Blade (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 21 m/s, and the yaw angle was held at 0°. The blade pitch angle was 3°. The rotor rotated at 72 RPM. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pretensioned to 40,000 N. During postprocessing, the probe channels were set to read –99999.99. The standard tip blocks were replaced with blade extensions that created a 5.532-m radius rotor as shown in Appendix A. The extension used the S809 airfoil throughout, and the linear taper of the blade continued along the extension. Note that the blade radius was not changed during post-processing so the pressure tap locations are at the same radial location, but the reference to 30% represents 30% of 5.029 m, not 5.532 m. Throughout this report, references to the blade span are made for the 5.029-m radius, not the 5.532-m radius.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 5 - Raw Data

Sequence 5: Sweep Wind Speed (F,P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed was ramped from 5 m/s to 25 m/s by the wind tunnel operator. This was repeated with a decreasing ramp. The yaw angle was maintained at 0°. The blade tip pitch was 3° or 6°. The rotor rotated at 72 RPM. Blade pressure and probe measurements were collected for both pitch angles. The five-hole probes were removed and the plugs were installed for another 3° pitch case. Plastic tape 0.03 mm thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. The 6- minute campaigns were named using the sequence designation 5, followed by DN or UP, which indicates the wind speed ramp direction. The next four digits are 0000, and the sequence digit is at the end.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence F - Raw Data

Sequence F: Downwind High Cone (F) This test sequence used a downwind, rigid turbine with an 18° cone angle. The wind speed ranged from 10 m/s to 20 m/s. Excessive inertial loading due to the high cone angle prevented operation at lower wind speeds. Yaw angles of ±20° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link was replaced with a shorter bar so the load cell was not installed during this test. However, the teeter link load cell channel was flagged as not applicable by setting the measured values in the data file to -99999.99 N.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 3 - Raw Data

Sequence 3: Tower Wake Measure (P) Sequence 3 used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s] Reynolds number regimes for the circular cross-section tower. The yaw angle and blade tip pitch angles were selected to traverse the probe tip across the tower wake, while keeping the probe axis approximately parallel to the tunnel centerline. The rotor was parked with the instrumented blade at 180° azimuth. Blade and probe pressure measurements were collected.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 4 - Raw Data

Sequence 4: Static Pressure Calibration (P) This test sequence used a downwind, teetered turbine with a 3.4° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 30° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected. A static pitot probe was installed on a boom 2.3 m upwind of the nacelle at hub height and connected to the reference side of the Mensor digital differential pressure transducer through the pneumatic rotary coupling. This provided the reference pressure for all blade-mounted pressure transducers, as opposed to the NASA atmospheric pressure reference that was used for all other test sequences. This simulates the pressure system connections used in field measurements where the static pressure was unknown.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 6 - Raw Data

Sequence 6: Shroud Wake Measure (P) This test sequence used a downwind, rigid turbine with a 3.4° cone angle. The wind speeds for this sequence corresponded to subcritical [7 m/s], transitional [15 m/s], and supercritical [20 m/s] Reynolds number regimes for the circular cross-section tower. The yaw angle and blade tip pitch angles were selected to traverse the probe tip across the tower wake while keeping the probe axis approximately parallel to the tunnel centerline. The rotor was parked with the instrumented blade at 180° azimuth. Blade and probe pressure measurements were collected. An airfoil-shaped aluminum shroud was placed on the tower below the 34% span five-hole probe. It extended below the 91% span five-hole probe. The turntable angle was adjusted to position the shroud at various angles relative to the flow.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 8 - Raw Data

Sequences 8 and 9: Downwind Sonics (F,P) and Downwind Sonics Parked (P) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s. Yaw angles of 0° to 60° were achieved. The blade tip pitch was 3°. The rotor rotated at 72 RPM during Sequence 8, but it was parked during Sequence 9. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. Sonic anemometers were mounted on a strut downwind of the turbine. The strut was mounted to the T-frame, which was rotated to align the anemometers aft of the 9% and 49% radius locations at hub height. Because of this configuration, the tunnel balance data are considered invalid. Sequence 9 was designed to compare the downwind sonic anemometer readings with the upwind sonic anemometers without interference from the turbine. The rotor was parked with the instrumented blade at 0° azimuth. All pressure measurements obtained in Sequence 9 are invalid because sufficient time for temperature stabilization did not occur, thus all associated data values were flagged as not applicable by setting the measured values in the data file to 0.0000 Pa. This test is further described in Appendix G.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence 9 - Raw Data

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence G - Raw Data

Sequence G: Upwind Teetered (F) Test sequence G used an upwind, teetered turbine with a 0° cone angle. The wind speeds ranged from 5 m/s to 25 m/s. Yaw angles of ±180° were achieved at low wind speeds and angles of ±10° were achieved at the high wind speeds. The blade tip pitch was 3°. The rotor rotated at 72 RPM. Blade and probe pressure measurements were collected.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence V - Raw Data

Sequence V: Tip Plate (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 25 m/s, and the yaw angle was held at 0°. The blade pitch angle was 3°. The rotor rotated at 72 RPM. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. The standard tip blocks were replaced with a tip plate to simulate the effect of an undeployed tip-mounted aerodynamic brake as shown in Appendix A. Note that the blade radius was not changed during post-processing so the pressure tap locations are at the same radial location, but the reference to 30% represents 30% of 5.029 m, not 4.943 m. Throughout this report, references to the blade span are made for the 5.029- m radius, not the 4.943-m radius.

17 WIND ENERGY↗

DOE OSTI2022

UAE6 - Wind Tunnel Tests Data - UAE6 - Sequence X - Raw Data

Sequence X: Elevated RPM (F) This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speed ranged from 5 m/s to 12 m/s, and yaw angles of ±30° were obtained. The blade pitch angle was 3°. The rotor rotated at 90 RPM. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read -99999.99. As described in Appendix F, the hydrostatic correction derived for operation at 72 RPM was applied to these data.

17 WIND ENERGY↗

DOE OSTI2021

Estimation of the Ambient Wind Field From Wind Turbine Measurements Using Gaussian Process Regression

In the search for a lower levelized cost of wind energy, one approach is to increase the accuracy of wind turbine measurements such as wind speed and wind direction. The sensors available on wind turbines are susceptible to local turbulence and measurement bias, which can result in suboptimal turbine performance. As an alternative, recent research has considered using the sensor measurements in a coordinated manner. With such a cooperative approach, the local wind conditions can be estimated more accurately and reliably without the need for additional measurement equipment. In this paper, a novel wind field estimation approach is presented that estimates the local wind conditions based on turbine measurements using Gaussian processes. We show that the estimation framework is able to improve the accuracy of the wind direction estimate both in an offline and online manner, as well as identify possible biases in the sensors and reduce unnecessary wind turbine yaw activity.

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

DOE OSTI2021

Deep Reinforcement Learning for Automatic Generation Control of Wind Farms

This paper provides a model-free framework for real-time control of wind farms to accurately track a power reference signal. This problem requires tractable dynamical models for capturing the aerodynamic interaction between wind turbines and controllers that can make decisions in realtime given varying atmospheric conditions. In this paper, we propose a deep reinforcement learning framework to provide real-time yaw control of a wind farm. Modifications have been made to FLOw Redirection and Induction in Steady State (FLORIS), a modeling tool that incorporates transient wake behavior. The control problem is formulated to track a synthetic power reference signal based on historical atmospheric (wind speed and direction) information, price signals, and regulation deployment data from U.S. regional transmission operators. Results indicate that a wind farm, with this control paradigm, can achieve good tracking performance when tested with real atmospheric data.

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

DOE OSTI2020

Multi-Scale Simulation of Wind Farm Performance during a Frontal Passage

Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. Here in this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

17 WIND ENERGY↗