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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Introduction to the Topical Collection on Regional Renewable Energy – Africa

The investments in and provision of power across the African continent are undergoing dramatic transitions brought on by unprecedented technological advances, falling generation costs, and utility business model changes. This transition, now at various stages across the diverse continent, will employ novel approaches and recognize a diverse group of energy users and decision makers - powering development with the region's abundant supply of renewable energy resources. Policymakers, planners, and the private sector in Africa, like those around the globe, are employing new approaches to take advantage of economically attractive renewable energy generation, ranging from innovations in distributed systems enabling higher penetrations of renewable energy, micro- and mini-grids powered entirely by solar photovoltaics and storage for energy access, to large-scale renewable power generation and grid and market integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

High Penetration Solar PV Deployment Sunshine State Solar Grid Initiative (SUNGRIN)

The report provides results from the Sunshine State Solar Grid Initiative (SUNGRIN) high penetration solar PV deployment project led by Florida State University’s (FSU) Center for Advanced Power Systems (CAPS). FSU CAPS and industry and university partners have completed a five-year effort aimed at enabling effective integration of high penetration levels of grid-connected solar PV generation. SUNGRIN has made significant contributions in the development of simulation-assisted techniques, tools, insight and understanding associated with solar PV effects on electric power system (EPS) operation and the evaluation of mitigation options for maintaining reliable operation. An important element of the project was the partnership and participation of six major Florida utilities and the Florida Reliability Coordinating Council (FRCC). Utilities provided details and data associated with actual distribution circuits having high-penetration PV to use as case studies. The project also conducted foundational work supporting future investigations of effects at the transmission / bulk power system level. In the final phase of the project, four open-use models with built-in case studies were developed and released, along with synthetic solar PV data sets, and tools and techniques for model reduction and in-depth parametric studies of solar PV impact on distribution circuits. Along with models and data, at least 70 supporting MATLAB functions have been developed and made available, with complete documentation.

14 SOLAR ENERGY↗
DOE OSTI2015

Sources of Operational Flexibility, Greening the Grid

Changes in electricity demand and generation must be constantly balanced to maintain power system stability and reliability. Operational flexibility refers to the ability of a power system to respond to these changes. Power systems are designed and operated to efficiently manage variability and uncertainty in electricity demand and resource availability. Variable renewable energy (VRE) increases this inherent variability and uncertainty, and thus increases the need for flexibility. Systems with significant variability and uncertainty require flexible generators that can rapidly change output, operate efficiently at lower outputs, and operate for short durations. This flexibility in turn can reduce the need to curtail (decrease the output of) solar and wind generation; improve investor confidence in VRE and revenue streams; decrease the risk of negative market pricing (which results when conventional generators cannot turn down to low outputs during times of high VRE output); and reduce environmental impacts by increasing system efficiency and maximizing the utilization of VRE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Conceptual Design for CLIC Gun Pulser

The Compact Linear Collider (CLIC) is a proposed future electron-positron collider, designed to perform collisions at energies from 0.5 to 5 TeV, with a nominal design optimized for 3 TeV (Dannheim, 2012). The Drive Beam Accelerator consists of a thermionic DC gun, bunching section and an accelerating section. The thermionic gun needs deliver a long (~143us) pulse of current into the buncher. A pulser is needed to drive grid of the gun to generate a stable current output. This report explores the requirements of the gun pulser and potential solutions to regulate grid current.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Influence of Multi-Dimension Heat Conduction on Heat Flux Calculation for HFIR LEU Analysis

Steady-state safety margins calculations are an important step in the evaluation of research reactor design. Margins for phenomena such as onset of nucleate boiling and critical heat flux are evaluated by comparing the heat flux leading to those phenomena to a local heat flux. Evaluating properly the magnitude of the heat flux is therefore important and can affect the design. Plate-type research reactors often exhibit significant power peaking on the edges of the plate, near the fuel/cladding interface. The magnitude of the heat flux calculated in these regions can be influenced by the size of the region in which they are evaluated but also by the ability to model heat transport in one or multiple dimensions. The present analysis studies the influence of these two parameters on the heat flux magnitude for the HFIR reactor. From this analysis, a fuel discretization grid is proposed that can generate one-dimension heat flux values relatively close to best estimate values obtained with a high-resolution grid and complex three-dimensional CFD modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Refinement of Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Computational simulations of the flow within a streamline-traced, external-compression supersonic inlet for Mach 1.664 without and with vortex generators were performed to refine the characterization of the inlet performance as measured by the total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. The refinement of the simulations concerned two aspects: 1) refinement of the grid for the simulations to evaluate and reduce uncertainty, and 2) refinement of the modeling and design of the vortex generators. The vortex generators studied were rectangular vane-type vortex generators arranged in co-rotating arrays within the subsonic diffuser. The vortex generator geometric factors of interest included the height, circumferential spacing, and angle-of-incidence. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vortex generators were simulated using either a vortex generator model or with grids generated about each vortex generator. Statistical methods were used to compute confidence intervals and grid convergence indices to establish the uncertainties of the analyses with respect to grid refinement. Design-of-experiments methods were applied to quantify the effects of the geometric factors of the vortex generators. The analyses of the computed results illustrate the complexities of quantifying the uncertainties of the inlet performance and the implications of the uncertainties for the design of a vortex generator array for the STEX inlet.

Slater, John W.↗
NASA NTRS2017

Imaging a Free-Geometry Magma Reservoir Using FEM-Based Linear Inverse Modeling of InSAR Data: Application to Rabaul Caldera, Papua New Guinea

We test an innovative inversion scheme using Green’s functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green’s function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluidfilled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green’s functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.

Inverse theory↗
NASA NTRS2017

Imaging the Complex Geometry of a Magma Reservoir Using Fem-Based Linear Inverse Modeling of InSAR Data: Application to Rabaul Caldera, Papua New Guinea

We test an innovative inversion scheme using Green’s functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green’s function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green’s functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the east side and of the past Vulcan volcano eruptions of more evolved materials on the west side. The interconnection and spatial distributions of sources correspond to the petrography of the volcanic products described in the literature and to the dynamics of the single and twin eruptions that characterize the caldera. The ability to image the complex geometry of deformation sources in both space and time can improve our ability to monitor active volcanoes, widen our understanding of the dynamics of active volcanic systems and improve the predictions of eruptions.

Inverse theory↗
DOE OSTI2018

2016 Renewable Energy Grid Integration Data Book

The 2016 Renewable Energy Grid Integration Data Book identifies the status, key trends, challenges, and solutions of renewable energy grid integration in a highly visual format. This data book provides an overview of selected key grid integration metrics that represent complex interactions among generation characteristics, market rules, and environmental and safety factors, which may vary by geography, season, and time of day; and presents metrics that either indicate how much variable renewable energy (VRE) is currently being integrated onto the grid, or measure factors that may increase or decrease the challenges associated with integrating VRE generation onto the grid.

variable, renewable, grid, integration, wind, sola↗
DOE OSTI2024

Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems

This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

This document presents a master–slave methodology for solving the problem of optimal operation of photovoltaic (PV) distributed generators (DGs) in direct current (DC) networks. This problem was modeled using a nonlinear programming model (NLP) that considers the minimization of three different objective functions in a daily operation of the system. The first one corresponds to the minimization of the total operational cost of the system, including the energy purchasing cost to the conventional generators and maintenance costs of the PV sources; the second objective function corresponds to the reduction of the energy losses associated with the transport of energy in the network, and the third objective function is related to the minimization of the total emissions of CO2 by the conventional generators installed on the DC grid. The minimization of these objective functions is achieved by using a master–slave optimization approach through the application of the Vortex Search algorithm combined with a matrix hourly power flow. To evaluate the effectiveness and robustness of the proposed approach, two test scenarios were used, which correspond to a grid-connected and a standalone network located in two different regions of Colombia. The grid-connected system emulates the behavior of the solar resource and power demand of the city of Medellín-Antioquia, and the standalone network corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá-Choco. A numerical comparison was performed with four optimization methodologies reported in the literature: particle swarm optimization, multiverse optimizer, crow search algorithm, and salp swarm algorithm. The results obtained demonstrate that the proposed optimization approach achieved excellent solutions in terms of response quality, repeatability, and processing times.

14 SOLAR ENERGY↗
DOE OSTI2020

Making coal relevant for small scale applications: Modular gasification for syngas/engine CHP applications in challenging environments

Small-scale coal gasification technology, coupled to a reciprocating engine generator, has the potential for making coal a cost competitive resource for meeting the flexible energy needs and resiliency requirements of utilities across the United States. To maintain grid stability and reliability, electrical generation must be regulated to match the load at the proper voltage and frequency. With the expansion of intermittent sources into the grid, such as wind and solar, frequency and voltage regulation become increasingly important and challenging. This work presents the results of a Front End Engineering Design (FEED) effort to detail the engineering and preliminary economics of a small-scale, air blown, fixed-bed gasification process, operating at near-atmospheric pressure, with gas cleanup to provide syngas and pyrolysis liquid fuels for use in reciprocating engine generators for combined heat and power at the University of Alaska Fairbanks. A very detailed assessment of capital and operating costs allows the evaluation of a levelized cost of electricity of 208.06 $/MWh, which can be reduced through the selling of by-products (steam for heating purposes and pyrolysis liquids to be used for power generation in an existing diesel engine). Here, a combined sensitivity analysis, based on the Monte Carlo approach, has been carried out to evaluate the effects of the uncertainties (capital and operating costs and plant annual availability) on the LCOE.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Testing GFM and GFL Inverters Operating With Synchronous Condensers

Inverter-based resources (IBRs) are quickly evolving into a source of reliability services to the electric grid. Penetration levels of variable generation are rapidly increasing, ranging from 60% -70% in some systems. To go further, a fundamental shift is required to address challenges associated with grid stability. Synchronous condensers (SCs) are considered an important complementary technology in such transitions. This paper provides one-of-a-kind insights into real experimental results from operating a real MW-scale system consisting of a 2.2-MVA grid-forming (GFM) and grid-following (GFL) battery energy storage system, 2.5-MVA SCs, and a 3-MVA load bank operating as a small, islanded grid. Challenges that are expected in larger systems were mimicked in this small but real system to demonstrate seamless transitions from one mode to another as well as stable operation with different combinations of GFM and GFM resources, including a "loss of last synchronous generator" case. The experimental results presented in this paper are a valuable resource to everyone involved in developing and validating models or developing controls of power systems consisting of inverters and synchronous condensers.

grid-following converter↗
DOE OSTI2020

Optimizing an Integrated Solar-Electrolysis System (CRADA CRD-18-749 Final Report)

Electrolysis powered by renewable sources provides a range of potential values such as carbon-free fuel for power, heat, or transportation; storage; and ancillary grid services. Each of these potential benefits has been studied as individual value streams. However, real-world demonstrations of these benefits working in concert are limited in the United States today as electrolyzers lack access to wholesale electricity prices. High power prices make electrolysis uncompetitive compared to traditional steam methane reformation (SMR). A potentially cost-effective way to demonstrate the value of renewable electrolysis is by powering an electrolyzer directly from a renewable generation source rather than from the electric grid. Integrated with a renewable generation source, the cost of fueling an electrolyzer is the opportunity cost of not selling power from the renewable plant to the grid - effectively, the wholesale electricity price. Additionally, an electrolyzer tied directly to a renewable generator potentially reduces excess generation and increases the value of the ancillary services that the renewable generator can provide to the grid.

08 HYDROGEN↗
DOE OSTI2023

Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting

Here, the growing usage of decentralized renewable energy sources has made accurate estimation of their aggregated generation crucial for maintaining grid flexibility and reliability. However, the majority of distributed photovoltaic (PV) systems are behind-the-meter (BTM) and invisible to utilities, leading to three challenges in obtaining an accurate forecast of their aggregated output. Firstly, traditional centralized prediction algorithms used in previous studies may not be appropriate due to privacy concerns. There is therefore a need for decentralized forecasting methods, such as federated learning (FL), to protect privacy. Secondly, there has been no comparison between localized, centralized, and decentralized forecasting methods for BTM PV production, and the trade-off between prediction accuracy and privacy has not been explored. Lastly, the computational time of data-driven prediction algorithms has not been examined. This article presents a FL power forecasting method for PVs, which uses federated learning as a decentralized collaborative modeling approach to train a single model on data from multiple BTM sites. The machine learning network used to design this FL-based BTM PV forecasting model is a multi-layered perceptron, which ensures privacy and security of the data. Comparing the suggested FL forecasting model to non-private centralized and entirely private localized models revealed that it has a high level of accuracy, with an RMSE that is 18.17% lower than localized models and 9.9% higher than centralized models.

14 SOLAR ENERGY↗
DOE OSTI2026

Modeling and Experimental Validation of a Direct-Contact Counter-Flow Fluidized Bed Heat Exchanger for Thermal Energy Storage (TES) Applications

Particle-based thermal energy storage (TES) systems are an emerging energy storage technology. The technological advances have reduced costs, making TES more competitive and reliable in the marketplace but an efficient and reliable operation is heavily dependent on coherent heat transfer between air to particles or vice versa. The particle-based TES technologies provide an intermediate system that can store energy for short (0-10 h), long (10-200 h) and seasonal (> 200 h) timescales. The TES systems store energy by converting electricity to thermal energy; electricity can be directly sourced intermittent generation technologies and/or the grid, helping manage peak loads and other mismatches in supply and demand. The overall efficiency of the TES system depends on the performance of system components (particle storage silos and particle transfer mechanism etc.). The particle heat exchanger is one of the key system components that affects the system efficiency. The pressurized fluidized bed heat exchanger (PFB HX) performance is challenging to predict due to the chaotic behavior of particle and fluid interaction. This research presents a computational study of a novel direct-contact, counter-flow and air-to-particles PFB HX, that contributes in advancing the particle-based long-duration TES technologies. For the current analysis an unsteady Eulerian-Eulerian CFD model was developed and validated against experiments performed at the National Laboratory of the Rockies for two particle sizes (600 ..mu..m and 825 ..mu..m ). Following validation, parametric simulations were conducted to evaluate the effects of interphase drag models (Syamlal-O'Brien and Gidaspow), particle size, bed height and the influence of a frictional-viscosity term on hydrodynamics and heat transfer between the air & particles. The key findings from the analysis are: (1) for the studied operating window Syamlal-O'Brien provides superior agreement with measured gas temperatures (errors generally < 10%) while Gidaspow shows large deviations for the coarse particle case; (2) model predictions are most sensitive in the lower 0.2 m above the air distributor where bubble initiation and local mixing dominate interphase heat transfer; (3) representation of the distributor (number of inlet ports) materially affects predicted local mixing and temperature stratification; and (4) the Eulerian-Eulerian framework reproduces bulk thermal trends but shows regime dependent limitations for coarse particles, motivating mesoscale informed closures for scale-up analysis for future studies. These results provide validated guidance for drag selection and distributor design in particle-based thermal energy storage applications. Collectively, the validated model and parametric results quantify key drivers of PHB-HX performance and provide practical guidance for design and optimization. The results provide confidence in the model predictability and provide a step forward to improve on heat exchange performance. The demonstrated performance and modeling approach support the deployment and further development of this novel PHB-HX concept for robust, particle-based long-duration thermal energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2025

A novel approach for large-scale wind energy potential assessment

Increasing wind energy generation is central to grid decarbonization, yet methods to estimate wind energy potential are not standardized, leading to inconsistencies and even skewed results. This study aims to improve the fidelity of wind energy potential estimates through an approach that integrates geospatial analysis and machine learning (i.e., Gaussian process regression). We demonstrate this approach to assess the spatial distribution of wind energy capacity potential in the Contiguous United States (CONUS). We find that the capacity-based power density ranges from 1.70 MW/km2 (25th percentile) to 3.88 MW/km2 (75th percentile) for existing wind farms in the CONUS. The value is lower in agricultural areas (2.73 ± 0.02 MW/km2, mean ± 95 % confidence interval) and higher in other land cover types (3.30 ± 0.03 MW/km2). Notably, advancements in turbine manufacturing could reduce power density in areas with lower wind speeds by adopting low specific-power turbines, but improve power density in areas with higher wind speeds (>8.35 m/s at 120m above the ground), highlighting opportunities for repowering existing wind farms. Wind energy potential is shaped by wind resource quality and is regionally characterized by land cover and physical conditions, revealing significant capacity potential in the Great Plains and Upper Texas. The results indicate that areas previously identified as hot spots using existing approaches (e.g., the west of the Rocky Mountains) may have a limited capacity potential due to low wind resource quality. Improvements in methodology and capacity potential estimates in this study could serve as a new basis for future energy systems analysis and planning.

Dai, Tao↗