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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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At least 325 records · Page 18

Hydrogen Production Cost with Anion Exchange Membrane Electrolysis

Rigorous stakeholder-vetted techno-economic analysis was performed to assess the cost of hydrogen (H 2 ) produced using state-of-the-art Anion Exchange Membrane (AEM) electrolysis. Projected high-volume, untaxed and unsubsidized levelized cost of hydrogen (LCOH)1 range from 2020 $\$$1.78 to $\$$3.68/kg H 2 depending on technology year, process design, and electrolyzer project scale, assuming an electricity price of $\$$0.03/kWh and a capacity factor of 97%. The total installed capital cost for an AEM electrolysis plant was estimated from bottom-up stack and process plant cost models. The stack cost model accounts for manufacturing equipment, equipment maintenance, material, tooling, cycle time, yield, labor, utilities and general overhead. The process plant cost model accounts for purchased equipment, installation costs, site preparation, and general overhead costs. For this study, the AEM electrolysis plant is assumed to be a stick-built, greenfield project developed by an engineering, procurement, and construction (EPC) firm with electrolysis stacks purchased directly from an electrolysis stack manufacturer. The price of the electrolysis stacks is based on a bottom-up cost assessment with business markup for the electrolysis company fabricator. Methods from the Hydrogen Analysis (H2A) production model, a peer-reviewed national laboratory-developed discounted cash flow (DCF) model, were used to calculate the production LCOH in 2020 $\$$/kg H 2 . The baseline electricity price case ($\$$0.03/kWh) corresponds to average wholesale electricity prices currently possible in U.S. markets with plentiful wind. Similar low-cost electricity pricing is possible from solar Power Purchase Agreements (PPA) although these prices are typically limited by renewable energy capacity factors.

08 HYDROGEN↗

A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry

Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗

Low cost textile-grade carbon-fiber epoxy composites for automotive and wind energy applications

Carbon fiber reinforced polymer composites are highly desirable for automotive and wind energy applications due to advantages associated with weight reduction, high stiffness and strength, durability, and recyclability. The high cost of carbon fiber has been a limiting factor in its widespread adoption in non-aerospace applications. A low cost (estimated < $11 per kg) wide tow (450-600k) carbon fiber derived from textile grade polyacrylonitirile precursor, and hence called Textile Grade Carbon Fiber (TCF) is introduced in this paper. Fundamental aspects of the TCF are discussed along with a detailed characterization of its mechanical properties. Two manufacturing processes relevant to automotive and wind energy applications are considered, namely-compression molding and resin infusion. Furthermore, at various stages the TCF has been compared to commercial non-aerospace 50k carbon fiber composite. Detailed physical and mechanical properties including tensile, flexural, compression, and interlaminar shear properties are reported and compared to non-aerospace carbon fiber composite. The results provide a means for designers and end-users in the automotive and wind energy sector to consider different forms of economical non-aerospace carbon fibers.

42 ENGINEERING↗

NREL’s Wind Turbine Drivetrain Condition Monitoring and Wind Plant Operation and Maintenance Research During the 2010s: A US Land-Based Perspective

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

17 WIND ENERGY↗

Big Adaptive Rotor Phase I Final Report

The Big Adaptive Rotor (BAR) project was initiated by the U.S. Department of Energy (DOE) in 2018 with the goal of identifying novel technologies that can enable large (>100 meter [m]) blades for low-specific-power wind turbines. Five distinct tasks were completed to achieve this goal: 1. Assessed the trends, impacts, and value of low-specific-power wind turbines; 2. Developed a wind turbine blade cost-reduction road map study; 3. Completed research-and-development opportunity screening; 4. Performed detailed design and analysis; and, 5. Assessed low-cost carbon fiber. These tasks were completed by the national laboratory team consisting of Sandia National Laboratories (Sandia), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory.

17 WIND ENERGY↗

Conceptual Designs of the Structure of Inflatable Blades for Enabling Larger Turbines

Over the last couple of decades, increasingly larger rotor diameters have enabled significant reductions in the levelized cost of energy for wind through higher energy capture and improved capacity factors. But for onshore turbines, this has been met with manufacturing and transportation challenges. To enable larger onshore rotors, an innovative inflatable blade concept is investigated that employs both traditional and onsite manufacturing. The design architecture consists primarily of an inflatable aerodynamic shell attached to a factory-manufactured primary structure. Multiple architectures, cross-sectional topologies, and material combinations for the primary structure are investigated, as well as multiple skin materials. Structural cross-sectional characteristics are compared to a traditional blade, and inflatability and cost evaluations are presented. Results show that a box-beam architecture using only composite materials yields significant mass reduction with mature technologies/processes and modest cost decrease compared to traditional blade construction. This low-TRL study demonstrates the inflatable blade concept's techno-economic potential.

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

Optimal short range trajectories for helicopters

An optimal flight path algorithm using a simplified altitude state model and an apriori climb-cruise-descent flight profile has been developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. The performance model is based on standard flight manual data and is such that on-line trajectory optimization is feasible with a relatively small computer. The results show that the optimal flight path and optimal cruise altitude can represent a 10 percent fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability due to helicopter weight, ambient winds and the relative cost trade-off between time and fuel. In general, 'reasonable' variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost.

Slater, G. L.↗

Great Lakes Wind Energy Challenges and Opportunities Assessment

Many issues associated with wind development in the Great Lakes will require solutions different from those developed for offshore wind in ocean states and may not fully benefit from the industry learnings of nearby states. As a result, technology readiness and cost reduction for Great Lakes Wind (GLW) energy generation is likely to be delayed relative to other regions without a substantial, targeted GLW research campaign, and proactive stakeholder engagement in the region at all levels. Failure to conduct the necessary research to lower GLW costs in the near term could limit its contribution to the Nation's decarbonization goals by 2035, and could potentially raise long term energy prices in Great Lakes states if demand for renewable energy continues to accelerate. The overall objective of a research program such as that described in this report would be to enable the realization of commercial GLW before 2035. With the aim of ensuring that prospective development of GLW is conducted efficiently, safely, and coordinated in the best interests of the local residents and stakeholders, the U.S. Department of Energy (DOE) Wind Energy Technologies Office (WETO) tasked the National Renewable Energy Laboratory (NREL) to assist in (a) developing an improved understanding of offshore wind power's development potential in the Great Lakes, (b) identifying the key issues that need to be resolved for this potential to be achieved, and (c) defining a comprehensive research program to address and resolve these issues. This report presents the results of NREL's effort to address these needs.

cost modeling↗

Comparison of wind farm control strategies under realistic offshore wind conditions: turbine quantities of interest

Abstract. Wind farm flow control is a strategy to increase the efficiency and therefore lower the levelized cost of energy of a wind farm. This is done using turbine settings such as the yaw angle, blade pitch angles, or generator torque to manipulate the flow behind the turbine, affecting downstream turbines in the farm. Two inherently different wind farm flow control methods have been identified in the literature: wake steering and wake mixing. This paper focuses on comparing the turbine quantities of interest between these methods for a simple two-turbine wind farm setup, while a companion article (Brown et al., 2025) focuses on the wake quantities of interest for a single wind turbine setup. Both papers use the same set of wind farm simulations based on high-fidelity large-eddy simulations (LESs) coupled with OpenFAST turbine models. First, precursor simulations are executed in order to match wind conditions measured with lidars in an offshore wind farm off the east coast of the USA. These measurements show general wind conditions that exhibit substantially higher vertical wind shear and veer than any of the LES studies performed with wind farm flow control strategies currently available in the literature. The precursors are used to evaluate the effectiveness of the control methods. In the LES, the wind veer leads to highly skewed wakes, which have considerable influence on the power uplift of wind farm flow control strategies. In addition to a baseline controller, four different control strategies, each of which uses either pitch or yaw control, are performed on the upstream turbine of a simple two-turbine wind farm. Assuming that the wind direction is known and constant over time, the simulations show that wake steering is generally the superior wind farm flow control strategy, considering both wind farm power production and turbine damage equivalent loads when substantial wind veer is present. This result is consistent over different wind speeds and wind directions. On the other hand, for similar wind conditions with lower veer, wake mixing was found to yield the highest power production, although at the expense of generally higher loads. This leads us to conclude that the effect of wind veer, which has so far not usually been considered, can not be neglected when determining the optimal wind farm flow control strategy.

17 WIND ENERGY↗

Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data

The wind energy industry is continuously improving their operational and maintenance practice for reducing the levelized costs of energy. Anticipating failures in wind turbines enables early warnings and timely intervention, so that the costly corrective maintenance can be prevented to the largest extent possible. It also avoids production loss owing to prolonged unavailability. One critical element allowing early warning is the ability to accumulate small-magnitude symptoms resulting from the gradual degradation of wind turbine systems. Inspired by the cumulative sum control chart method, this study reports the development of a wind turbine failure detection method with such early warning capability. Specifically, the following key questions are addressed: what fault signals to accumulate, how long to accumulate, what offset to use, and how to set the alarm-triggering control limit. We apply the proposed approach to 2 years’ worth of Supervisory Control and Data Acquisition data recorded from five wind turbines. We focus our analysis on gearbox failure detection, in which the proposed approach demonstrates its ability to anticipate failure events with a good lead time.

17 WIND ENERGY↗

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

Abstract This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21 % . Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5 % . Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3 % without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.

17 WIND ENERGY↗

Activating Opportunity Zones for Rapid Solar+Storage Deployment in Low Income Communities (Final Report)

Millions of Texans choose their own power provider, giving them the option to have low-cost and even renewable energy delivered through their retail electric plan. However, Texans with less disposable income often pay more for electricity and have limited access to green energy and emergency backup power even though the costs of solar and wind power are at record lows and continue to decline. The Powered for Good initiative aimed to help deliver clean, affordable, 100% renewable electricity to low-income households in Texas’s Competitive Retail Areas, where households can choose their electricity provider. Objectives: The primary goal of this project was to develop and validate one or more affordable solar+storage products (i.e., priced less than of $0.14/kWh) that Retail Electricity Providers (REP) can offer to LI households. The team achieved three objectives: 1. Investigate how to best reduce electricity costs and increase availability of emergency power for LI customers; 2. Build momentum for, and facilitate an approach to, a Texas-based pilot deployment of such solar+storage products, with a goal of greatly expanding this approach to a large segment of the LI population in Texas; 3. Provide the structural framework, finance model, and roadmap to potentially increase investment of solar+storage projects in LI communities across U.S. states when modified to meet their state-specific laws and regulations. The team evaluated the market of viable solutions for low-income Texans through interviews and focus groups with professionals and residents with lived experience. The team then piloted a low-cost retail electric product. Following the pilot, the team developed educational materials, including fact sheets, a Go Green Save Green interactive guide, and an Electricity Bill Analysis Tool. The team is now working to increase power resilience and reduce energy insecurity with micro solar and storage in partnership with local entities in the Harris County area. Key Findings: Informed by Powered for Good research, including the experiences on Texas residents and electricity system experts, the Powered for Good team developed a pilot that was implemented by Energy Well Texas, a new company formed in late 2020. The pilot featured a combination of a 100% clean residential energy offering delivered through the electrical grid plus a selection of batteries, lights and a solar panel that provided participants with varying levels of backup power. For the 8 customers who submitted previous bills, the Energy Well Texas pilot reduced energy bills by about 30%. In Houston, residents earning less than 30% of Area median Income (AMI) spend an average 13% of their income on energy or about $1,555 per year. Repeating the pilot results for these residents could yield $466 in savings per customer or about 4% of their income. While this will not end energy poverty, it is a big step toward that goal. The Powered for Good and Energy Well Texas teams are currently planning their post-pilot phase of service offerings.

14 SOLAR ENERGY↗

Scale-Resolving Simulations of a Supersonic Retro-Propulsion Concept For Mars Entry, Descent, and Landing

Supersonic retro-propulsion (SRP) is a deceleration technology that could enable largerpayloads and potentially humans to be brought from space to the surface of Mars safely.Accurate and reliable CFD predictions are needed to help design future Mars entry, descent,and landing (EDL) vehicles due to the cost and limitations of wind tunnel tests. TypicalCFD approaches struggle at points along the Mars EDL trajectory with high enough altitude(low enough ambient pressure) that the SRP motor plumes are over-expanded. This workdemonstrates how high-order scale-resolving simulations on Cartesian AMR grids can provideaccurate and reliable time-averaged aerodynamic loads on the vehicle for this challengingflow regime. Greater than second order convergence in the time-averaged integrated axialforce𝐶𝐴is obtained across the three finest mesh resolutions simulated, and the estimateduncertainty is smaller than the unsteady standard deviation – demonstrating the accuracy andreliability of the method. Although costly, this approach can yield higher confidence in𝐶𝐴thanpreviously obtained in a reasonable turnaround time and is within reach for a few points in thetrajectory (i.e. Mach 2.4, 2.52, and 2.78). Further computational performance and numericalmethods improvements are needed to reduce the cost enough to bring this method into the EDLengineering design cycle.

S&M↗

Renewable Energy Contingencies in Power Systems: Concept and Case Study

This paper introduces the concept of renewable energy contingencies that represent long-term/extended variability of variable renewable energy (VRE) resources, namely, significant periods (e.g., days/weeks) of low wind/solar availability. These contingencies have not received much attention to date but are likely to emerge as a major issue in some countries such as India as the share of VRE increases. Using 38 years of climate model reanalysis data for wind over India, we demonstrate that low periods of wind contingency below long-term (Indian) national average of 5 m/s can extend for more than 100 days in several zones some of which are deploying large wind farms. Even in some of the best wind resource areas in India with long term average wind speed close to 7 m/s, low wind days (e.g., 5 m/s which is substantially below average) can extend up to 60 days. We propose a four-step methodology around a co-optimization based energy-ancillary services dispatch model to assess the impact of renewable contingency and implemented it for the state of Tamil Nadu, the most wind-rich state of India. We have estimated that annual renewable contingency cost impact of 5 GW additional wind in Tamil Nadu to be in the range of US$27-76 million pa. Planning analysis should embrace the concept of renewable contingency to recognize these costs and put in place necessary spinning reserve and back-up generation resources.

Mohar Chattopadhyay↗

Optimal short-range trajectories for helicopters

An optimal flight path algorithm using a simplified altitude state model and a priori climb cruise descent flight profile was developed and applied to determine minimum fuel and minimum cost trajectories for a helicopter flying a fixed range trajectory. In addition, a method was developed for obtaining a performance model in simplified form which is based on standard flight manual data and which is applicable to the computation of optimal trajectories. The entire performance optimization algorithm is simple enough that on line trajectory optimization is feasible with a relatively small computer. The helicopter model used is the Silorsky S-61N. The results show that for this vehicle the optimal flight path and optimal cruise altitude can represent a 10% fuel saving on a minimum fuel trajectory. The optimal trajectories show considerable variability because of helicopter weight, ambient winds, and the relative cost trade off between time and fuel. In general, reasonable variations from the optimal velocities and cruise altitudes do not significantly degrade the optimal cost. For fuel optimal trajectories, the optimum cruise altitude varies from the maximum (12,000 ft) to the minimum (0 ft) depending on helicopter weight.

Slater, G. L.↗

The design of low cost structures for extensive ground arrays

The development of conceptual designs of solar array support structures and their foundations including considerations of the use of concrete, steel, aluminum, or timber are reported. Some cost trends were examined by varying selected parameters to determine optimum configurations. Detailed civil/structural design criteria were developed. Using these criteria, eight detailed designs for support structures and foundations were developed and cost estimates were made. As a result of the study wind was identified as the major loading experienced by these low height structures, whose arrays are likely to extend over large tracts of land. Proper wind load estimating is considered essential to developing realistic structural designs and achieving minimum cost support structures. Wind tunnel testing of a conceptual array field was undertaken and some of the resulting wind design criteria are presented. The SPS rectenna system designs may be less sensitive to wind load estimates, but consistent design criteria remain important.

Franklin, H. A.↗

Repurposing Inactive Oil and Gas Wells for Energy Storage: Maximizing the Potential Via Optimal Drivetrain Control: Preprint

In recent years, there has been a growing emphasis on utilizing energy storage to enhance grid resilience against disruptive events. While renewable energy supply continues to expand, gravity-based solutions like pumped hydro remain dominant in the commercial space. However, their geographical limitations constrain availability, scalability, and increase costs for co-locating solar and wind energy. An alternative approach proposes repurposing idle oil and gas wells located closer to existing grid infrastructure, offering a promising and cost-effective solution. This paper addresses the optimization and control of a regenerative drive system coupled to an interior permanent magnet synchronous machine in a 300-meter well with a 100-Newton weight. The study employs a dynamic MATLAB/Simulink model to simulate the operation of the electric drivetrain system during storage and discharge operations. The results demonstrate an initial round-trip efficiency of 85.9% for the electrical system alone and identify crucial factors for maximizing efficiency. The optimized operation and control of the electromechanical drivetrain system hold great potential for minimizing the levelized cost of storage while maximizing efficiency and revenue generation.

ENERGY STORAGE,ENGINEERING↗

Wind Turbine Contingency Control Through Generator De-Rating

Maximizing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. In that context, systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage to the turbine. Advanced contingency control is one way to enable autonomous decision-making by providing the mechanism to enable safe and efficient turbine operation. The work reported herein explores the integration of condition monitoring of wind turbines with contingency control to balance the trade-offs between maintaining system health and energy capture. The contingency control involves de-rating the generator operating point to achieve reduced loads on the wind turbine. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.

condition monitoring↗