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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 1,009 records · Page 56

Near wake evolution of a tidal stream turbine due to asymmetric sheared turbulent inflow with different integral length scales

Tidal stream turbines deployed at highly energetic open water sites are subjected to sheared inflow in the rotor plane. The inflow shear is expected to cause asymmetric loading on the rotor blades and affect the downstream wake. In the current study, two different turbulent inflow conditions, static-high shear and dynamic shear, were generated via an active-grid turbulence generator. A 1:20 scaled three-bladed horizontal axis tidal turbine model was tested in those conditions. The results were compared to a quasi-laminar case with no imposed turbulence or shear. The results show that the high shear reduces the average performance, with a drop of up to 16% in the optimal power coefficient. Besides, the shear profiles increase torque fluctuations and induce significant differences in wake hydrodynamics between the high-speed (upper) and low-speed (lower) regions. The large integral length scales further enhance the load fluctuations perceived by the rotor but have a negligible effect on the mean wake field quantities and the wake recovery. The lower half region featured a faster breakdown of tip vortex structure and a rapid drop of swirl number, a phenomenon conjectured to be a consequence of the strong turbulence intensities and Reynolds stresses in the lower half region. Furthermore, the sheared turbulent inflow also results in a very intensive energy redistribution process towards large-scale, low-frequency motions, which is important to the downstream turbines.

16 TIDAL AND WAVE POWER↗

Design of energy storage system to improve inertial response for large scale PV generation

With high-penetration levels of renewable generating sources being integrated into the existing electric power grid, conventional generators are being replaced and grid inertial response is deteriorating. This technical challenge is more severe with photovoltaic (PV) generation than with wind generation because PV generation systems cannot provide inertial response unless special countermeasures are adopted. To enhance the inertial response, this paper proposes to use battery energy storage systems (BESS) as the remediation approach to accommodate the degrading inertial response when high penetrations of PV generation are integrated into the existing power grid. A sample power system was adopted and simulated using PSS/E software. Here, impacts of different penetration levels of PV generation on the system inertial response were investigated and then BESS was incorporated to improve the frequency dynamics.

25 ENERGY STORAGE↗

A global marching technique for the prediction of separated flows over arbitrary airfoils

The flow over arbitrary airfoils is analyzed using a boundary-layer-type solver developed for studying separated flows. The scheme includes extension to a general coordinate system and use of a more general zonal technique for solving the coupled equations. In order to be able to consider arbitrary geometries, second order accurate (in space) conservative differences are generated by considering the integral formulation of the governing equations in a general coordinate system. The general coordinate system is handled in as general a manner as possible to allow for the use of either analytically or numerically generated coordinate system. Different C type grids (orthogonal and nonorthogonal) were generated using different grid generation techniques to analyze the flow over arbitrary airfoils (J012, J025, NACA0012). A comparison with the experiment is demonstrated.

Halim, Ahmad A. M.↗

Generation of three-dimensional unstructured grids by the advancing-front method

The generation of three-dimensional unstructured grids using the advancing-front technique is described. While this generation technique has been shown to be effective for the generation of unstructured grids in two dimensions, its extension to three-dimensional regions required the development of surface definition software and sophisticated data structures to avoid excessive CPU-time overheads for the search operations involved. After obtaining an initial triangulation of the surfaces, tetrahedrons are generated by successively deleting faces from the generation front. Details of the mesh generation algorithm are given, together with examples and timings.

Lohner, Rainald↗

Experimental Characterization Test of a Grid-Forming Inverter for Microgrid Applications

Standardized experimental testing protocols for grid forming (GFM) inverters to ensure expected operation under both normal and contingency conditions do not exist. Such protocols increase the confidence of system owner/operators that an inverter deployed in a proposed system will engage in typical behaviors to ensure interoperability with other units and ancillary equipment (e.g. protection equipment). This paper presents systematic and comprehensive test protocols to evaluate the performance of GFM inverters under the following operational configurations: islanded operation, heterogeneous islanded operation (parallel with a synchronous generator), grid-connected operation, and transition operation. A commercial GFM inverter is used to verify the test protocols and to understand the inverter's performance and functionalities. In particular, required configuration and tuning of the inverter will be explained in the full paper to enrich the testing protocol.

black start↗

Smart Grid and Smart Cities

We hope the proceedings will offer the readers a good opportunity to explore the state-of-the art developments and future directions of researches on smart grid and smart cities. These conferences covered the recent trends and progresses made in the field of smart grid and smart cities. For the past few years, smart grids have been one of the main topics in research and development at academic, industry, business and government level. The smart grid is envisaged to be the next generation electric grid for Smart Cities. It enables the smart integration of conventional power generation, renewable generation, distributed generation, energy storage, transmission, distribution and demand management. The benefits of smart grid include the enhanced reliability and resilience, higher intelligence and optimized control, decentralized operation, higher operational efficiency, more efficient demand management, and better power quality. However, all these prospected transformations also bring with them numerous challenges and opportunities. The conference program covers keynotes, invited, oral and poster presentations. The keynotes and invited talks are focused on the potential application of smart grid and smart cities in various fields of application. Among 105 full length articles submitted to the conference, 59 manuscripts were accepted after a thorough peer reviews and were recommended for presentations and publication in this proceedings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Performance Evaluation of a Microgrid System with Grid-Forming and Grid-Following Inverters with Diesel Generators: Insights From Hardware Experiments

This paper presents a comprehensive performance evaluation of a microgrid system integrating grid-forming (GFM) inverters, grid-following (GFL) inverters, and a diesel generator, focusing on their interactions and behavior under various dynamic events. The study is conducted using a pure hardware setup comprising two GFM inverters, one GFL inverter, a diesel generator, load banks, a point of common coupling (PCC), and an emulated main grid. The evaluation specifically examines dynamic scenarios, including voltage jumps, phase jumps, rate of change of frequency (ROCOF), synchronization, and islanding operations, which pose critical challenges to system stability. Among all the tests conducted, the overloading and phase jump tests proved to be the most challenging. The capacity of the DC side is crucial for withstanding overloading and grid disturbance tests; otherwise, GFM inverters frequently trip due to DC undervoltage. Throughout all grid disturbance tests, the diesel generator consistently stands out as the most robust and reliable GFM unit in the system. Overall, insights from these hardware experiments shed light on the response characteristics of different generation types during grid disturbances and identify potential stability concerns in such hybrid microgrid systems.

14 SOLAR ENERGY↗

Single block three-dimensional volume grids about complex aerodynamic vehicles

This paper presents an alternate approach for the generation of volumetric grids for supersonic and hypersonic flows about complex configurations. The method uses parametric two-dimensional block-face grid definitions, within the framework of GRIDGEN2D. The incorporation of a face decomposition reduces complex surfaces to simple shapes. These simple shapes are recombined to obtain the final face definition. The advantages of this method include the reduction of overall grid generation time through the use of vectorized computer code, the elimination of generating matching block faces, and simplified boundary conditions.

Alter, Stephen J.↗

Impact Analysis of Utility-Scale Energy Storage on the ERCOT Grid in Reducing Renewable Generation Curtailments and Emissions

This paper explores the solutions for minimizing renewable energy (RE) curtailment in the Texas Electric Reliability Council of Texas (ERCOT) grid. By utilizing current and future planning data from ERCOT and the System Advisor Model from the National Renewable Energy Laboratory, we examine how future renewable energy (RE) initiatives, combined with utility-scale energy storage, can reduce CO2 emissions while reshaping Texas’s energy mix. The study projects the energy landscape from 2023 to 2033, considering the planned phase-out of fossil fuel plants and the integration of new wind/solar projects. By comparing emissions under different load scenarios, with and without storage, we demonstrate storage’s role in optimizing RE utilization. The findings of this paper provide actionable guidance for energy stakeholders, underscoring the need to expand wind and solar projects with strategic storage solutions to maximize Texas's RE capacity and substantially reduce CO2 emissions.

14 SOLAR ENERGY↗

Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.

Etingov, Pavel↗

Adaptive hybrid prismatic-tetrahedral grids for viscous flows

The paper presents generation of adaptive hybrid prismatic/tetrahedral grids for complex 3-D geometries including multi-body domains. The prisms cover the region close to each body's surface, while tetrahedra are created elsewhere. Two developments are presented for hybrid grid generation around complex 3-D geometries. The first is a new octree/advancing front type of method for generation of the tetrahedra of the hybrid mesh. The main feature of the present advancing front tetrahedra generator that is different from previous such methods is that it does not require the creation of a background mesh by the user for the determination of the grid-spacing and stretching parameters. These are determined via an automatically generated octree. The second development is an Automatic Receding Method (ARM) for treating the narrow gaps in between different bodies in a multiply-connected domain. This method is applied to a two-element wing case. A hybrid grid adaptation scheme that employs both h-refinement and redistribution strategies is developed to provide optimum meshes for viscous flow computations. Grid refinement is a dual adaptation scheme that couples division of tetrahedra, as well as 2-D directional division of prisms.

Kallinderis, Yannis↗

Energy Efficiency and Distributed Generation for Resilience: Withstanding Grid Outages for Less

Communities across the United States experience extreme weather-related events that lead to disruptions in electric service. In 2017 alone, the nation experienced droughts, floods, freezes, hurricanes, and wildfires that cumulatively cost over $300 billion in damages and led to longer and more frequent disruptions in power. Without on-site backup power, these disruptions endanger public safety, security, and health. To better prepare for future disruptions, state and local governments are reducing the electric demand of their critical operations through energy efficiency, as well as making new investments in microgrids with distributed generation to ensure continuous electric supply during extended grid outages to power critical facilities. This resource describes how energy efficiency can be integrated planning for microgrids for resilience at critical public facilities, lowering the cost of a new system that can sustain operation during a grid outage. It includes real world examples as well as modeled scenarios to illustrate how efficiency can achieve energy and cost savings.

grid energy, power outages, microgrid, distributed↗

Enhancing power grid resilience to winter storms via generator winterization with equity considerations

Here we develop two-stage stochastic programming models for generator winterization that enhance power grid resilience while incorporating social equity. The first stage in our models captures the investment decisions for generator winterization, and the second stage captures the operation of a degraded power grid, with the objective of minimizing load shed and social inequity. To incorporate equity into our models, we propose a concept called adverse effect probability that captures the disproportionate effects of power outages on communities with varying vulnerability levels. Grid operations are modeled using DC power flow, and equity is captured through mean or maximum adverse effects experienced by communities. We apply our models to a synthetic Texas power grid, using winter storm scenarios created from the generator outage data from the 2021 Texas winter storm. Our extensive numerical experiments show that more equitable outcomes, in the sense of reducing adverse effects experienced by vulnerable communities during power outages, are achievable with no impact on total load shed through investing in winterization of generators in different locations and capacities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗

Quantifying Socioeconomic Impacts of Electricity Generating Technologies

The levelized cost of energy (LCOE) and other cost metrics used in energy planning do not account for out-of-market impacts of the technology choice. While a decision-maker at the utility or asset owner level may compare multiple forms of electricity generating technology using LCOE, a decision-maker over energy policy or community stakeholders may be interested in considering impacts beyond those that LCOE measures. This report quantifies economic impacts such as jobs and wage growth across electricity generation technologies then develops an approach to systematically compare socioeconomic metrics across technology choices. To address additional workforce related impacts, this report also compares the typical workforce education requirements and annual income levels for multiple types of electricity generating facilities. The grid scale electricity generating technologies analyzed in this report produce power using conventional hydroelectric dams, coal, natural gas, nuclear reactors, solar PV, land-based wind turbines, geothermal heat, and woody biomass combustion. Although it doesn’t generate electricity itself, the economic impacts associated with battery storage equipment manufacturing and installation were also analyzed.

03 NATURAL GAS↗

A multiple-block multigrid method for the solution of the three-dimensional Euler and Navier-Stokes equations

A multiple block multigrid method for the solution of the three dimensional Euler and Navier-Stokes equations is presented. The basic flow solver is a cell vertex method which employs central difference spatial approximations and Runge-Kutta time stepping. The use of local time stepping, implicit residual smoothing, multigrid techniques and variable coefficient numerical dissipation results in an efficient and robust scheme is discussed. The multiblock strategy places the block loop within the Runge-Kutta Loop such that accuracy and convergence are not affected by block boundaries. This has been verified by comparing the results of one and two block calculations in which the two block grid is generated by splitting the one block grid. Results are presented for both Euler and Navier-Stokes computations of wing/fuselage combinations.

Atkins, Harold↗

An adaptive grid method for computing time accurate solutions on structured grids

The solution method consists of three parts: a grid movement scheme; an unsteady Euler equation solver; and a temporal coupling routine that links the dynamic grid to the Euler solver. The grid movement scheme is an algebraic method containing grid controls that generate a smooth grid that resolves the severe solution gradients and the sharp transitions in the solution gradients. The temporal coupling is performed with a grid prediction correction procedure that is simple to implement and provides a grid that does not lag the solution in time. The adaptive solution method is tested by computing the unsteady inviscid solutions for a one dimensional shock tube and a two dimensional shock vortex iteraction.

Bockelie, Michael J.↗