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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Status Update: Deposition Modeling For SNF Canister CISCC

This report fulfills the M3 milestones M3SF-21PN010207025 & M3SF-20PN0102070412. During fiscal year (FY) 2020, Pacific Northwest National Laboratory (PNNL) worked to further develop the FY 2019 deposition and particle tracking models. This status report outlines these efforts and presents the progress made so far. Model development work is ongoing and is planned to continue in FY 2021. The FY 2020 model development included work on: Wind Effects. Model development and sensitivity studies, investigated how wind direction and speed affect deposition; Brownian Motion. Implementing Brownian Motion into existing models; Particle Size Variability. Depending on the particle composition, the diameter of the particle may vary with changes in relative humidity. Models were developed to analyze this; Multiphase and Fluid Film Modeling. Investigating canister surface wetting and drying, and how this effects overall deposition. Models were developed to analyze this; Difusophoresis. Performing initial work to implement diffusiophoresis into the existing models; Turbophoresis. Performing initial work to implement turbophoresis into the existing models. Much of this work will continue into FY21. The authors present initial results and discus current and future work.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Validation of new and existing methods for time-domain simulations of turbulence and loads

We seek to obtain a second-by-second match between the simulated and measured structural loads of a utility-scale wind turbine. To obtain the one-to-one load simulations, we start with the furthest upstream component of the modeling chain: the turbulent inflow. We consider new and existing methods to generate constrained-turbulence flow fields. The new method is based on large-eddy simulations (LES) and machine learning (ML). The existing methods include Kaimal-based TurbSim and the superstatistical wind field model. The inflow measurements used to constrain these simulations are obtained with a nacelle-mounted scanning lidar. We compare the flow fields for the different inflow simulation approaches and validate their associated load predictions against measurements collected in the Rotor Aero-dynamics, Aeroelastics, and Wake (RAAW) field campaign. We find that the rotor-position control developed for this study is key in enabling the time match between measurements and simulations. When this control approach is used, the load simulation performance tracks with the inflow simulation fidelity, with LES+ML yielding errors ≤ 4% for the damage-equivalent loads of flapwise bending moment, and tower fore-aft bending moments.

17 WIND ENERGY↗
DOE OSTI2021

Robust Output Feedback Control Design for Inertia Emulation by Wind Turbine Generators

Wind generation has gained widespread use as a renewable energy source. Most wind turbines and other renewables connected to the grid through converters result in a reduction in the natural inertial response to grid frequency changes. The doubly-fed induction generator (DFIG) can be controlled to compensate for this reduction and, in fact, provide faster response than traditional synchronous machines. This paper proposes to design observer based output feedback linear quadratic regulator (LQR) and H control laws to realize the inertia emulation function and deliver fast frequency support. Furthermore, the aim is to track the reference speed by a diesel synchronous generator (DSG) in order to reach the desired inertia. The control signal is computed based on a reduced order model using the balanced truncation technique. A comparison with selective modal analysis (SMA) and balanced truncation model reduction techniques is presented. Comprehensive results show the effective emulation of synthetic inertia by implementing the control laws on a nonlinear three- phase diesel-wind system. The proposed technique is analyzed for different short circuit ratio (SCR) scenarios.

17 WIND ENERGY↗
DOE OSTI2026

Recent Increasing Trend in October–November Caribbean Tropical Cyclone Activity

October–November Caribbean tropical cyclone (TC) activity has significant impacts for both the Caribbean islands and Central America (e.g., Hurricanes Eta and Iota in 2020). October–November Caribbean TCs can also track northward and make continental United States landfall, resulting in substantial damage and fatalities (e.g., Hurricane Michael in 2018 and Delta and Zeta in 2020). We find significant increasing trends in October–November Caribbean hurricanes, rapidly intensifying hurricanes (winds increasing by ≥15 m s −1 within 24 hr), and landfalling hurricanes during the global satellite era (1979–present). Since 1979, we also observe significant warming trends in the western Atlantic Warm Pool and anomalous relative cooling in the eastern Pacific during October–November. These trends yield a more conducive dynamic and thermodynamic environment for Caribbean TCs, including reductions in Caribbean vertical wind shear, increases in Caribbean potential intensity, and a more TC-conducive African easterly jet.

Klotzbach, P. J. [Colorado State Univ., Fort Colli↗
DOE OSTI2025

Uncertainty in Synthetic Tropical Cyclone Hazard and Risk Estimates: Insights from RAFT, CHAZ, MIT, STORM, and CLIMADA

We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗
DOE OSTI2024

Avian Radar / Processed Data

This dataset contains radar track data of avian targets from DeTect's 7360 s-band radar during the large barge deployment from June 2024 though September 2024.

17 WIND ENERGY↗
DOE OSTI2022

Hybrid Power Plants: Status of Operating and Proposed Plants, 2022 Edition [Slides]

Falling battery prices and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data mined from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes co-located hybrid plants that pair two or more generators and/or that pair generation with storage at a single point of interconnection, and full hybrids that feature co-location and co-control. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2021, there were nearly 300 hybrid plants (>1 MW) operating across the United States, totaling nearly 36 gigawatts (GW) of generating capacity and 3.2 GW/8.1 GWh of energy storage. PV+storage plants are by far the most common, dominating in terms of plant number (140), storage capacity (2.2 GW/7.0 GWh), storage:generator ratio (53%), and storage duration (3.2 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was a breakout year for PV+storage hybrids in particular: 67 of the 74 hybrids added in 2021 were PV+storage. By the end of 2021, there were more GW of battery capacity installed in PV+storage hybrids (2.2 GW) than as standalone storage plants (1.8 GW). The difference is even starker in energy terms, with PV+storage plants hosting twice as much battery capacity as standalone storage plants (7 GWh vs. 3.5 GWh, respectively). Much of the battery capacity added in hybrid form in 2021 was a battery retrofit to a pre-existing PV plant. -Data on plants under development from the interconnection queues of all seven ISOs/RTOs plus 35 individual utilities suggest that these hybridization trends are likely to continue. At the close of 2021, there were more than 670 GW of solar plants in the nation’s queues; 285 GW (~42%) of this capacity was proposed as a hybrid, most typically pairing PV with battery storage (PV+storage represented nearly 90% of all hybrid capacity in the queues). For wind, 247 GW of capacity sat in the queues, with 19 GW (~8%) proposed as a hybrid, again most-often pairing wind with storage (wind+storage represented ~4% of all hybrid capacity in the queues). Meanwhile, nearly half of all storage in the queues is estimated to be part of a hybrid plant. While many of these proposed plants will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Hybrid Power Plants: Status of Operating and Proposed Plants, 2024 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis.

14 SOLAR ENERGY↗
DOE OSTI2026

High-Resolution Large-Eddy Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the Large-Eddy simulations. The data will be divided according to the storm intensity level at the simulation time. Category 2: Harvey, Nate Category 3: Michael, Delta Category 4: Michael, Laura

17 WIND ENERGY↗
DOE OSTI2026

High-Resolution Mesoscale Simulations of Historical U.S. Gulf Coast Hurricanes

This dataset provides coupled mesoscale and microscale (large-eddy simulation; LES) atmospheric simulations of five historical U.S. Gulf Coast hurricanes. Meso-microscale coupled simulations of Hurricanes Harvey (2017), Nate (2017), Michael (2018), Laura (2020), and Delta (2020) were performed with the Weather Research and Forecasting (WRF) model v4.1.5. The mesoscale component captures the multi-day evolution of each storm's track, intensity, and large-scale structure across the Gulf of Mexico, while the LES component explicitly resolves the dominant turbulent eddies in the hurricane boundary layer at a horizontal grid spacing of 33.33 m. Together, these simulations characterize tropical cyclone wind fields across atmospheric scales ranging from ~100 km down to ~100 m, spanning storm intensities from Category 2 through Category 4 on the Saffir–Simpson scale. This dataset contains the mesoscale simulations, separated by each storm.

17 WIND ENERGY↗
DOE OSTI2025

Long-Term Photovoltaic System Performance in Cold, Snowy Climates

As countries around the world transition towards renewable energy, there is increasing interest in using photovoltaic (PV) technologies to help decarbonize northern and alpine communities due to their scalability and affordability. However, a barrier to large-scale adoption of PV in cold climates is long-term performance uncertainty under snowfall, freeze-thaw cycles, low temperatures, and high winds. In this work, we provide a comprehensive review of published silicon degradation rates in cold Koppen-Geiger climate classifications of Dfb (humid continental), Dfc (subarctic), and ET (tundra). We first analyze the system degradation rates of three subarctic ground-mounted photovoltaic sites in North America using the RdTools year-on-year method: an Al-BSF double-axis tracking site in Fairbanks, Alaska (65degrees N); a PERC and silicon heterojunction bifacial vertical and south-tilted site in Fairbanks, Alaska; and a PERC south-facing fixed-tilt site in Fort Simpson, Northwest Territories (62degrees N). Degradation rates of these newly analyzed sites vary between -0.4%/year and -1.5%/year. Combining these data with previously reported cold climate degradation rates, we show that the distribution of cold climate degradation peaks at -0.1%/year to -0.2%/year but has a large tail with rates above -0.5%/year. The average reported cold climate degradation rate is -0.45%/year, whereas the median value is -0.33%/year. These results suggest that despite frequent freeze-thaw cycles and potential exposure to high wind and snow loads, PV systems in cold climates tend to degrade slower than PV systems in warmer climates. The limited sample size of reported degradation rates in cold climates (27) motivates the need for further data acquisition and monitoring efforts as new technologies are deployed.

14 SOLAR ENERGY↗
DOE OSTI2023

Hybrid Power Plants: Status of Operating and Proposed Plants, 2023 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2022, there were 374 hybrid plants (>1 MW) operating across the United States (+25% compared to the end of 2021), totaling nearly 41 GW of generating capacity (+15%) and 5.4 GW/15.2 GWh of energy storage (+69%/+88%). PV+storage plants are by far the most common, dominating in terms of plant number (213), storage capacity (4.0 GW/12.5 GWh), storage:generator capacity ratio (49%), and storage duration (3.1 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was another strong year for PV+storage hybrids in particular: 59 of the 62 hybrids added in 2022 were PV+storage. As of the end of 2022, there was roughly as much storage capacity operating within PV+storage hybrid plants as in standalone storage plants (~4 GW each). In storage energy terms, however, PV+storage edged out standalone storage by ~2 GWh (12.5 GWh vs. 10.4 GWh, respectively). -Interconnection queue data show continued strong developer interest in hybridization. At the close of 2022, there were 51% more hybrid plants—representing 59% more generating capacity—in interconnection queues across the United States than there were at the end of 2021. Solar dominates these proposed plants as well: at the close of 2022, there were 457 GW of solar capacity proposed as a hybrid (representing ~48% of all solar capacity in the queues), most typically pairing PV with battery storage. At the same time, there were 24 GW of wind capacity proposed as a hybrid (representing ~8% of all wind capacity in the queues), again most-often pairing wind with storage. Meanwhile, more than half of all storage in the queues is estimated to be part of a hybrid plant. While many of the plants proposed in the queues will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable, particularly in certain regions. For example, in CAISO, 97% of all solar capacity and 45% of all wind capacity in the queues is proposed as a hybrid. -The report also surveys power purchase agreement (PPA) price data from a sample of operating and proposed PV+storage plants. Though PV+storage PPA prices have fallen over time, “levelized storage adders” have recently increased somewhat to ~$\$ $7000/MW-month, ~$\$ $60/MWh-stored (assuming one full cycle per day), or ~$\$ $15/MWh-PV. Some of the recent price increase could simply reflect a trend towards higher battery:PV capacity ratios over time, which increases costs, all else being equal. The well-publicized impact of inflationary and supply chain pressures on battery prices is no doubt a contributor as well.

25 ENERGY STORAGE↗
DOE OSTI2024

Monsoonal MCS Initiation, Rainfall, and Diurnal Gravity Waves over the Bay of Bengal: Observation and a Linear Model

Abstract Previous observational studies have indicated that mesoscale convective systems (MCSs) contribute the majority of precipitation over the Bay of Bengal (BoB) during the summer monsoon season, yet their initiation and propagation remain incompletely understood. To fill this knowledge gap, we conducted a comprehensive study using a combination of 20-yr satellite observations, MCS tracking, reanalysis data, and a theoretical linear model. Satellite observations reveal clear diurnal propagation signals of MCS initiation frequency and rainfall from the west coast of the BoB toward the central BoB, with the MCS rainfall propagating slightly slower than the MCS initiation frequency. Global reanalysis data indicate a strong association between the offshore-propagating MCS initiation frequency/rainfall and diurnal low-level wind perturbations, implying the potential role of gravity waves. To verify the hypothesis, we developed a 2D linear model that can be driven by realistic meteorological fields from reanalysis. The linear model realistically reproduces the characteristics of offshore-propagating diurnal wind perturbations. The wind perturbations, as well as the offshore propagation signals of MCS initiation frequency and rainfall, are associated with diurnal gravity waves emitted from the coastal regions, which in turn are caused by the diurnal land–sea thermal contrast. The ambient wind speed and vertical wind shear play crucial roles in modulating the timing, propagation, and amplitude of diurnal gravity waves. Using the linear model and satellite observations, we further show that the stronger monsoonal flows lead to faster offshore propagation of diurnal gravity waves, which subsequently control the offshore propagation signals of MCS initiation and rainfall. Significance Statement Rainfall over the Bay of Bengal (BoB) is primarily contributed by large and organized rainfall systems in the summer monsoon season. During this season, these systems are commonly observed over the east coast of India around midnight, the western BoB in the morning, and the central BoB in the afternoon. This eastward rainfall propagation is confirmed by observations, reanalysis data, and a theoretical model to have a strong association with atmospheric diurnal gravity waves. These waves are caused by land–sea thermal contrast and can trigger rainfall systems over the offshore regions. We also found that the diurnal gravity waves, as well as their triggered rainfall systems, can be greatly modulated by the large-scale monsoonal flows. All the above findings improve our understanding of diurnal rainfall cycle over the BoB and may contribute to the future improvement of rainfall forecast over the region.

Meteorology & Atmospheric Sciences↗
DOE OSTI2025

The Remarkable 2024 North Atlantic Mid‐Season Hurricane Lull

Abstract The 2024 North Atlantic (hereafter Atlantic) hurricane season started quickly, with the earliest Category 5 on record (Beryl) and three hurricanes forming through 14 August. Following Ernesto's dissipation on 20 August, the Atlantic hurricane season became extremely quiet during the climatological peak of hurricane season, with only one Category 2 hurricane (Francine) and one tropical storm through 23 September. Several environmental factors likely contributed to this unexpected, prolonged lull. During mid‐to‐late August, subseasonal conditions were broadly favorable for Atlantic hurricanes, but a northward shift in African easterly wave emergence latitude yielded fewer tropical cyclone seed disturbances that also traversed unfavorably cool ocean water. During early‐to‐mid September, subseasonal variability driven by the Madden‐Julian oscillation was less conducive to hurricane activity, with several bouts of increased vertical wind shear across the central Atlantic. Throughout most of the lull, the tropical Atlantic was anomalously dry and subsident, suppressing hurricane formation chances. Plain Language Summary The 2024 North Atlantic (hereafter Atlantic) hurricane season was anticipated to be extremely active, with seasonal forecasts calling for a potentially historic season. Following a busy start including the earliest Category 5 Atlantic hurricane on record (Beryl), the season became very quiet between 20 August–23 September, with only one Category 2 hurricane (Francine) and one tropical storm forming. Following the lull, the Atlantic became extremely busy again, with seven hurricanes forming from 25 September through the end of the season–the most on record for this period. This paper focuses on the surprising lull and attributes it to several different factors, including a late‐August northward shift in African easterly wave tracks (organized thunderstorm complexes spanning thousands of kilometers that often serve as Atlantic hurricane seeds). This northward shift brought these systems out over colder water and into a drier airmass, suppressing their hurricane formation chances. During the first 3 weeks of September, a large‐scale tropical phenomenon known as the Madden‐Julian oscillation, resulted in increased sinking motion, drier mid‐levels and increased vertical wind shear–all of which typically reduce Atlantic hurricane activity. Overall, the lull demonstrates how seed disturbances and other environmental factors can strongly modulate aggregate seasonal tropical cyclone activity. Key Points Following an active start, the 2024 Atlantic hurricane was quiet during the climatological peak with only 1 tropical storm and 1 hurricane The lull was not anticipated by seasonal forecasting agencies, which called for an extremely active 2024 Atlantic hurricane season Factors reducing storm count included a northward shift in African easterly waves, broad‐scale subsidence, and reduced mid‐level moisture

Klotzbach, P J↗
DOE OSTI2024

Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller's performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.

axial flow↗