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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Solar wind control of auroral zone geomagnetic activity

Solar wind magnetosphere energy coupling functions are analyzed using linear prediction filtering with 2.5 minute data. The relationship of auroral zone geomagnetic activity to solar wind power input functions are examined, and a least squares prediction filter, or impulse response function is designed from the data. Computed impulse response functions are observed to have characteristics of a low pass filter with time delay. The AL index is found well related to solar wind energy functions, although the AU index shows a poor relationship. High frequency variations of auroral indices and substorm expansions are not predictable with solar wind information alone, suggesting influence by internal magnetospheric processes. Finally, the epsilon parameter shows a poorer relationship with auroral geomagnetic activity than a power parameter, having a VBs solar wind dependency.

Clauer, C. R.↗
DOE OSTI2020

A Clustering-Based Scenario Generation Framework for Power Market Simulation with Wind Integration

A critical step in stochastic optimization models of power system analysis is to select a set of appropriate scenarios and significant numbers of scenario generation methods exist in the literature. This paper develops a clustering based scenario generation method, which aims to improve the performance of existing scenario generation techniques by grouping a set of correlated wind sites into clusters according to their cross-correlations. Copula based models are utilized to model spatiotemporal correlations and the Gibbs sampling is then used to generate scenarios for day-ahead markets. Our results show that the generated scenarios based on clustered wind sites outperform existing approaches in terms of reliability and sharpness and can reduce the total computational time for scenario generation and reduction significantly. The clustering-based framework can therefore provide a better support for real-world market simulations with high wind penetration.

data visualization↗
DOE OSTI2021

Computational Math Problems for a Clean Energy Future

Cutting edge computational mathematics are ubiquitous in renewable energy research. Problems in resilient and reliable electric grid operations, infrastructure planning, wind farm yaw control, and more demand sophisticated and scalable computational tools that enable the transition of renewable energy technologies from proof of concept to deployment into our energy system. The mission of the Computational Science Center at NREL is to lead the lab's efforts to solve energy challenges using high-performance computing (HPC), computational science, applied mathematics, scientific data management, visualization, and informatics. In this poster, we provide a short overview of three areas of computational mathematics research at NREL: wind power scenario generation for stochastic grid operations and infrastructure planning, improved rational function approximations for electromagnetic transients codes, and wind farm yaw control using a combination of the Alternating Direction Method of Multipliers (ADMM) and reinforcement learning (RL). Increasing penetrations of renewable energy into power grids motivate the investigation of new approaches to characterizing uncertainty for five-minute economic dispatch problems. Similarly, as the penetration of distributed energy resources on power grids increases, it becomes important to revisit our methods of modelling transient phenomena, i.e. electromagnetic transients programs. Finally, the combination of ADMM and RL for wind farm yaw control presented here can potentially increase the efficiency of the deployed distributed controllers by orders of magnitude.

ADMM↗
DOE OSTI2017

Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations

With increasing wind power penetration in the electricity grid, system operators are recognizing the need for additional flexibility, and some are implementing new ramping products as a type of ancillary service. However, wind is generally thought of as causing the need for ramping services, not as being a potential source for the service. In this paper, a multi-timescale unit commitment and economic dispatch model is developed to consider the wind power ramping product (WPRP). An optimized swinging door algorithm with dynamic programming is applied to identify and forecast wind power ramps (WPRs). Designed as positive characteristics of WPRs, the WPRP is then integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. Numerical simulations on the modified IEEE 118-bus system show the potential effectiveness of WPRP in increasing the economic efficiency of power system operations with high levels of wind power penetration. It is found that WPRP not only reduces the production cost by using less ramping reserves scheduled by conventional generators, but also possibly enhances the reliability of power system operations. Moreover, wind power forecasts play an important role in providing high-quality WPRP service.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Economic Justification of Concentrating Solar Power in High Renewable Energy Penetrated Power Systems

Concentrating solar power (CSP) plants are able to provide both renewable energy and operational flexibility at the same time due to its thermal energy storage (TES). It is ideal generation to power systems lacking in flexibility to accommodate variable renewable energy (VRE) generation such as wind power and photovoltaics. However, its investment cost currently is too high to justify its benefit in terms of providing renewable energy only. In this paper we evaluate the economic benefit of CSP in high renewable energy penetrated power systems from two aspects: generating renewable energy and providing operational flexibility to help accommodating VRE. In order to keep the same renewable energy penetration level during evaluation, we compare the economic costs between the system with a high share of VRE and another in which some part of the VRE generation is replaced by CSP generation. The generation cost of a power system is analyzed through chronological operation simulation over a whole year. The benefit of CSP is quantified into two parts: (1) energy benefit - the saving investment of substituted VRE generation and (2) flexibility benefit - the reduction in operating cost due to substituting VRE with CSP. The break-even investment cost of CSP is further discussed. The methodology is tested on a modified IEEE RTS-79 system. The economic justifications of CSP are demonstrated in two practical provincial power systems with high penetration of renewable energy in northwestern China, Qinghai and Gansu, where the former province has massive inflexible thermal power plants but later one has high share of flexible hydro power. The results suggest that the CSP is more beneficial in Gansu system than in Qinghai. The levelized benefit of CSP, including both energy benefit and flexibility benefit, is about 0.177-0.191 $/kWh in Qinghai and about 0.238-0.300 $/kWh in Gansu, when replacing 5-20% VRE generation with CSP generation.

14 SOLAR ENERGY↗
DOE OSTI2015

Flexible operation of batteries in power system scheduling with renewable energy

The fast growing expansion of renewable energy increases the complexities in balancing generation and demand in the power system. The energy-shifting and fast-ramping capability of energy storage has led to increasing interests in batteries to facilitate the integration of renewable resources. In this paper, we present a two-step framework to evaluate the potential value of energy storage in power systems with renewable generation. First, we formulate a stochastic unit commitment approach with wind power forecast uncertainty and energy storage. Second, the solution from the stochastic unit commitment is used to derive a flexible schedule for energy storage in economic dispatch where the look-ahead horizon is limited. Here, analysis is conducted on the IEEE 24-bus system to demonstrate the benefits of battery storage in systems with renewable resources and the effectiveness of the proposed battery operation strategy.

25 ENERGY STORAGE↗
DOE OSTI2022

Comparative Study of Wind Energy Potential Estimation Methods for Wind Sites in Togo and Benin (West Sub-Saharan Africa)

The characterization of wind speed distribution and the optimal assessment of wind energy potential are critical factors in selecting a suitable site for wind power plants (WPP). The Weibull distribution law has been used extensively to analyze the wind characteristics of candidate WPP sites, and to estimate the available and deliverable energy. This paper presents a comparative study of five wind energy resource assessment methods as they applied to the context of wind sites in West Sub-Saharan Africa. We investigated three numerical approaches, namely, the adaptive neuro-fuzzy inference system (ANFIS), the multilayer perceptron method (MLP), and support vector regression (SVR), to derive the distribution law of wind speeds and to optimally quantify the corresponding wind energy potential. Next, we compared these three approaches to two well-known Weibull distribution law-based methods: the empirical method of Justus (EMJ) and the maximum likelihood method (MLM). Case study results indicated that the neural network-based methods, ANFIS and MLP, yielded the most accurate distribution fits and wind energy potential estimates, and consequently, are the most recommended methods for the wind sites in Togo and Benin. The orders of magnitude of the root mean squared error (RMSE) in estimating the recoverable energy using ANFIS were, respectively, 10-4 and 10-5 for Lomé and Cotonou, while MLP achieved an RMSE order of magnitude of 10-3 for both sites.

17 WIND ENERGY↗
NASA NTRS1980

Composite rotor blades for large wind energy installations

The design of large wind power systems in Germany is reviewed with attention given to elaboration of the total wind energy system, aerodynamic design of the rotor blade, and wind loading effects. Particular consideration is given to the development of composite glass fiber/plastic or carbon fiber/plastic rotor blades for such installations.

Kussmann, A.↗
DOE OSTI2022

Wind Shear and Wind Veer Effects on Wind Turbines

This chapter highlights key contributions to the scientific literature on the sources of wind shear and wind veer in the atmospheric boundary layer, observations of shear and veer, and the effects of shear and veer on wind turbine power production, wind turbine wake evolution, and wind turbine loads. As wind turbines have grown larger, they encounter deeper and more complicated regions of the atmosphere. Over this height, profiles of wind speed shear and wind direction veer play a quantifiable role. Changes in the wind speed and wind direction across the vertical extent of a wind turbine rotor disk modify the inflow vector on the blades of the turbine, thereby affecting the magnitude and orientation of the lift and drag forces of the blade's airfoil. These changes can affect the power production and loads on large modern turbines, as well as the evolution of the wake that could affect a downwind turbine.

atmospheric stability↗
DOE OSTI2021

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↗
DOE OSTI2013

NREL Software Aids Offshore Wind Turbine Designs (Fact Sheet)

NREL researchers are supporting offshore wind power development with computer models that allow detailed analyses of both fixed and floating offshore wind turbines. While existing computer-aided engineering (CAE) models can simulate the conditions and stresses that a land-based wind turbine experiences over its lifetime, offshore turbines require the additional considerations of variations in water depth, soil type, and wind and wave severity, which also necessitate the use of a variety of support-structure types. NREL's core wind CAE tool, FAST, models the additional effects of incident waves, sea currents, and the foundation dynamics of the support structures.

17 WIND ENERGY↗
DOE OSTI2019

NREL's Balance-of-System Cost Model for Land-Based Wind

NREL's Land-based Balance of System Systems Engineering (LandBOSSE) model is a tool for modeling the balance of system (BOS) costs of land-based wind plants. BOS costs currently account for approximately 30% of the capital expenditures needed to install a land-based wind plant and include all costs associated with installing a wind plant, such as permitting, labor, material, and equipment costs associated with site preparation, foundation construction, electrical infrastructure, and tower installation. NREL developed LandBOSSE after identifying a need for a hybrid of process-based and empirically derived model that can provide flexibility for assessing wind plant BOS costs at a system level. NREL's prior BOS models have relied on empirical fits of legacy industry data, which limit their predictive ability. LandBOSSE, however, was designed to help users explore tradeoffs between innovative design scenarios while balancing the level of detail and speed required for model execution. The model was developed using a hybrid of process-based and empirically derived methods to create a modular model design that will allow for updates as wind energy technology evolves. The goal of LandBOSSE is to allow researchers, analysts, wind power developers, government agencies, and the public to explore how BOS may vary for different wind plant designs.

17 WIND ENERGY↗
DOE OSTI2017

Transforming Wind Turbine Blade Mold Manufacturing with 3D Printing

Innovation in the design and manufacturing of wind power generation components continues to be critical. As a result of this challenge, DOE’s Wind Energy Technologies Office (WETO) and Advanced Manufacturing Office (AMO), both within EERE, are partnering with public and private organizations to apply additive manufacturing, commonly known as 3D printing, to the production of wind turbine blade molds. The traditional method of blade design requires the creation of a plug, or a full-size representation of the final blade, which is then used to make the mold. Creating the plug is one of the most time-intensive and labor-intensive processes in wind blade construction, saving time and money.

3D printing↗
NASA NTRSDate not supplied

Identifying Optimal Site Location for Wind Energy Farms Considering Ecological and Social Impacts

With the increasing cost and declining availability of fossil fuels, renewable energy, specifically wind power, has become one of the fastest growing sources of energy in New Mexico. To assist with the goals set by the state’s Renewables Standard Portfolio established in 2004, the NASA DEVELOP team created three Optimal Wind Farm Suitability maps that consider social impact, ecological impact, and power production efficiency. The team utilized datasets from February 2013 – May 2018 that show vulnerable species, average wind patterns, and US Air Force Base locations. These three maps were combined into a final suitability map for optimal wind farm placement.

Joy Marich↗
DOE OSTI2015

Probabilistic Density Function Method for Stochastic ODEs of Power Systems with Uncertain Power Input

Wind and solar power generators are commonly described by a system of stochastic ordinary differential equations (SODEs) where random input parameters represent uncertainty in wind and solar energy. The existing methods for SODEs are mostly limited to delta-correlated random parameters (white noise). Here we use the Probability Density Function (PDF) method for deriving a closed-form deterministic partial differential equation (PDE) for the joint probability density function of the SODEs describing a power generator with time-correlated power input. The resulting PDE is solved numerically. A good agreement with Monte Carlo Simulations shows accuracy of the PDF method.

PDF method, stochastic differential equations, pow↗
DOE OSTI2022

Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches

Abstract Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.

17 WIND ENERGY↗
DOE OSTI2022

Blackstart Capability and Survivability of Wind Turbines with Fully Rated Converters

We report the blackstart capability of wind turbines is critical for the recovery of wind-dominant power systems from blackouts. If wind power plants are not able to restore a power system, the incorporation of wind resources into electric grids could be limited by blackstart capability. This paper tackles this problem by setting forth a grid-forming controller for Type 4 wind turbines which employ fully rated power converters. To this end, we engineer two-axis anti-windup proportional-integral regulators that serve to ride through restoration disturbances. We also design an active protection system to prevent wind turbines from stalling during recovery from blackouts. We demonstrate in a high-fidelity simulation environment that Type 4 wind turbines with the developed controllers and protection subsystem can: (i) re-energize a notional wind-dominant grid; (ii) ride through asymmetrical faults; and (iii) survive low wind speed events.

17 WIND ENERGY↗
DOE OSTI2024

Integrating in situ environmental covariates in an American lobster catch model to improve impact assessment

The installation and operation of floating offshore wind power is an integral component of societal transition to renewable energy generation where fixed bottom offshore wind is not possible. However, it will cause unique ecosystem changes. To disentangle the effects of offshore wind installations from the concurrent effects of climate change and the fishing practices on commercially significant resources, we must develop detailed characterizations of the resources before development occurs. In the Gulf of Maine, American lobster is the most commercially and culturally important fishery. At the time of writing, this is the largest fishery by value in North America. Our understanding of baseline localized parameters (such as catch per trap at the spatial scale of individual turbines) should be informed by relationships to environmental, biological, and survey-specific functional drivers of catch. A more mechanistic understanding of catch will allow for strategic adjustments to Post- Deployment fishery responses and ultimately, the development of research- and commercial-scale floating offshore wind development. Here, we used survey data from the New England Aqua Ventus Pre-Construction Commercial Trapping Survey to develop Generalized Additive Models describing seasonal catch per trap for legal and sublegal lobsters. We found fall catch to be nearly twice that of spring. Bottom temperature dynamics could be used to predict catch, and the Fall survey was associated with a warmer temperature regime. By using analytical tools that incorporate environmental heterogeneity, we developed monitoring methods from preconstruction baseline data that will be applicable over the post-construction operating period of an offshore wind farm.

BACI↗