Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “High Renewable Penetration”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

EUREICA: Efficient UltRa Endpoint IoT-enabled Coordinated Architecture

The electricity grid has evolved from a physical system to a cyber-physical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) that include renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. The purpose of this project was to develop a framework ((Efficient, Ultra-REsilient, IoT-Coordinated Assets, or EUREICA)for achieving grid resilience through suitably coordinated assets including a network of Internet of Things (IoT) devices, and a local electricity market (LEM) to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. Experiments conducted during this project demonstrated that, with this SA, a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. The demonstrations were carried out using a variety of high-fidelity co-simulation platforms, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

14 SOLAR ENERGY↗
DOE OSTI2025

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗
DOE OSTI2020

A Replacement Cold Neutron Guide System for HFIR (Conceptual Design Report)

The design of a replacement cold neutron guide system for the High Flux Isotope Reactor (HFIR) is presented. The proposed six-channel design uses the latest technologies and is optimally designed to account for operational and site constraints. These include the design of the cold source and the beam tube, the size and shape of the penetrations in the reactor confinement boundary, and the shape and orientation of the guide hall. The existing user instruments are a macromolecular diffractometer (IMAGINE), an IMAGING station, two small-angle neutron scattering (SANS) instruments (Bio-SANS and GP-SANS), and a cold triple-axis spectrometer (C-TAX). These instruments will all be reinstalled at end-of-guide positions with improved performance, and a position for a new high-performance neutron spin echo instrument will be created. The proposed guide design requires an extension to the guide hall toward the south. The calculated flux gain for a typical experiment is between a factor of 1.3 and 3 for all instruments, with the exception of the C-TAX instrument, which stands to gain a factor of >30 in flux at the sample. The new guide system will also offer additional performance gains, such as an increase in Q-range on Bio-SANS. The stated performance gains do not take into account any potential performance gains resulting from renewal and realignment of the guide system. The design of the guide system in the common sections up to about 25 m from the source is considered to be complete and ready for engineering design, while the designs of the instrument-specific guides are in some cases still a work in progress. The present report describes the current status of those designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Data and Multistage Optimization for the New Grid

Three essential capabilities for using exascale computing resources on next generation power grid applications are: generating large renewable energy datasets, modeling damage and operations during and after extreme events, and employing multi-stage optimization for infrastructure planning. Powerscenarios, developed as part of the ExaSGD project, addresses these capabilities by enabling users to build synthetic wind farms for large test systems using numerical weather prediction-based data sources. We share examples of using Powerscenarios to build out wind farms on the ACTIVSg2000 test system, to enable simulated operations and emergency asset allocation during a hurricane strike, and to compute multi-stage infrastructure buildouts.

economic dispatch↗
DOE OSTI2021

ROP model for PDC bits in Geothermal drilling

Geothermal energy is a renewable source of energy, where heat extraction is preferentially balanced with the reservoir's natural heat recharge rate. The objective of this paper is to present and validate a novel rate of penetration (ROP) model for drilling hard and abrasive formations including granite formations for polycrystalline diamond compact (PDC) bits. The ROP model was developed based on a derived relationship of a threshold weight on cutter (WOC) and its corresponding depth of cut (DOC) for a single cutter. Laboratory data was used to scale the derived single cutter relationship to a full-hole ROP model for PDC bits. The ROP model includes a non-linear correlation for Phase I (inefficient drilling due to low WOB values) and a linear Phase II (efficient drilling) ROP response to WOB. The ROP model was verified using measured drilling parameter data from Utah FORGE well# 58-32 and data from Chocolate Mountains well # 17-8 in Southern California. When compared to oil and gas well drilling, geothermal drilling in granitic formations can be more difficult and complicated due to rock hardness and high temperatures. PDC bits can increase ROP and optimize drilling for these types of hard formations. This paper provides novel insight into the ROP response of PDC bits to drilling operational parameters.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Multi-Fidelity Gaussian Process for Distribution System Voltage Probabilistic Estimation with PVs

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches.

distribution system estimation↗
DOE OSTI2020

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

distribution network↗
DOE OSTI2022

Numerical and Experimental Investigations on the Ignition Behavior of OME

On the path towards climate-neutral future mobility, the usage of synthetic fuels derived from renewable power sources, so-called e-fuels, will be necessary. Oxygenated e-fuels, which contain oxygen in their chemical structure, not only have the potential to realize a climate-neutral powertrain, but also to burn more cleanly in terms of soot formation. Polyoxymethylene dimethyl ethers (PODE or OMEs) are a frequently discussed representative of such combustibles. However, to operate compression ignition engines with these fuels achieving maximum efficiency and minimum emissions, the physical-chemical behavior of OMEs needs to be understood and quantified. Especially the detailed characterization of physical and chemical properties of the spray is of utmost importance for the optimization of the injection and the mixture formation process. The presented work aimed to develop a comprehensive CFD model to specify the differences between OMEs and dodecane, which served as a reference diesel-like fuel, with regards to spray atomization, mixing and auto-ignition for single- and multi-injection patterns. The simulation results were validated against experimental data from a high-temperature and high-pressure combustion vessel. The sprays’ liquid and vapor phase penetration were measured with Mie-scattering and schlieren-imaging as well as diffuse back illumination and Rayleigh-scattering for both fuels. To characterize the ignition process and the flame propagation, measurements of the OH* chemiluminescence of the flame were carried out. Significant differences in the ignition behavior between OMEs and dodecane could be identified in both experiments and CFD simulations. Liquid penetration as well as flame lift-off length are shown to be consistently longer for OMEs. Zones of high reaction activity differ substantially for the two fuels: Along the spray center axis for OMEs and at the shear boundary layers of fuel and ambient air for dodecane. Additionally, the transient behavior of high temperature reactions for OME is predicted to be much faster.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and Knowledge Gaps

The objective of this assessment was to leverage current medium- and heavy-duty vehicle (MHDV) data and information to evaluate the state of commercial vehicle electrification technologies, including the following: 1. Assessment and inventory of current MHDV electrification architectures; 2. Identification and assessment of MHDV component technologies; 3. Assessment of potential performance and cost drivers; and, 4. Identification of R&D gaps where appropriate R&D and technology would accelerate commercial vehicle electrification. These gaps include shortfalls in technology, gaps in data, and inadequate knowledge and understanding. To inform this study, the National Renewable Energy Laboratory–Oak Ridge National Laboratory team examined the open literature; conducted workshops; assessed and analyzed data on more than 175 electrified MHDVs, including vehicle and powertrain specifications; and conducted one-on-one meetings with industry representatives. This systems-level information was concatenated and parsed with respect to key characteristics such as battery energy, power, and range compared across vehicle classes. Operational data of many conventional vehicles were also examined to help determine the requirements on electrified vehicle attributes such as range. Previous studies on the total cost of ownership of electrified MHDVs were reviewed to determine where improvements in technologies (efficiency, cost, maintenance) were needed to accelerate adoption. The team also assessed the state of the art in electric drivetrains for component specifications and challenges for the commercial vehicle sector, including electric machines, power electronics, and off-board high-power charging systems (extreme fast charging and beyond). The goal of this analysis was to identify the barriers to widespread adoption of commercial vehicle electrification technologies and prioritize the research and development gaps that need to be overcome to accelerate significant market penetration of these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Sustainable hydrogen manufacturing via renewable-integrated intensified process for refueling stations

The widescale consumer adoption of hydrogen fuel cell electric vehicles (HFCEVs) is currently hindered by the high cost of small-scale hydrogen generation and the lack of extensive hydrogen refueling infrastructure. Natural gas-based hydrogen is cheaper when produced in large volumes but is also associated with high CO 2 emissions. To counter these challenges, we propose a hybrid approach where both natural gas and renewables are integrated in a synergistic manner using a dynamic process intensification technology that can be deployed on-site for meeting local demands of refueling stations. The technology is based on sorption enhanced steam methane reforming (SE-SMR) that utilizes a combination of reaction with in-situ CO 2 adsorption for enhancing process modularity, productivity and efficiency thereby outperforming conventional SMR at small scale. We develop a mixed integer linear programming (MILP)-based optimization framework for simultaneous design and scheduling of the SE-SMR process. The simultaneous optimization provides a synergistic combination whereby the renewables allow sustainable hydrogen manufacturing and the dynamic SE-SMR allows optimal use of the intermittency of the renewables. The U.S. nationwide analysis indicates that for futuristic renewable prices and a hydrogen production capacity of 2 ton/day, hydrogen can be produced at 50% less cost compared to the current cost of small-scale hydrogen generation. Finally, the city-wise analysis with varying hydrogen demand shows that even with just 5% HFCEV market penetration level, hydrogen production cost less than $3/kg can be obtained at small scales across the United States with even cheaper hydrogen for large cities.

08 HYDROGEN↗
DOE OSTI2023

Adaptive Deep Reinforcement Learning Algorithm for Distribution System Cyber Attack Defense With High Penetration of DERs

With grid modernization, smart inverters are increasingly used to execute advanced controls for distribution network reliability. However, this also increases the cyber-attack space. Here this paper focuses on the defense approaches to restore the system to normal operation circumstances in the presence of cyber-attacks. A unique deep reinforcement learning (DRL) method is developed to minimize voltage violations and reduce power losses for impacted feeders. The defense problem is reformulated as a Markov decision-making process to dynamically control DERs while minimizing load shedding. This is achieved via an improved soft actor-critic (SAC)-based DRL algorithm, which can govern DER set points and load-shedding scenarios in discrete and continuous modes via the auto-tune entropy and Gaussian policy features. Numerical comparison results on the modified IEEE 123-node system with other control approaches, such as Volt-VAR (VV), Volt-Watt (VW), and model predictive control (MPC) show that the proposed method can eliminate voltage violations and provide feasible control actions that perform complete mitigation of cyber-threats.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Electrical Systems of Pumped Storage Hydropower Plants: Electrical Generation, Machines, Power Electronics, and Power Systems

Adjustable-speed (AS) pumped storage hydropower (PSH) technology has the potential to become a large, consistent contributor to grid stability enabling higher penetrations of wind and solar energy on the future U.S. power system. AS-PSH has high-value characteristics, such as fast response to provide ancillary services to the grid, because it is a power converter interface with the grid (like battery storage), but at the same time it has the energy content large enough to supply both short-term (seconds-to-minutes) and long-term (minutes-to-hours) of energy needs, like more conventional power plants. However, designs must be optimized to lower the capital expenditure (CapEx) and to provide a high-quality grid interface capability (e.g. power quality, ancillary service provider, fault-tolerant or fault ride-through capability), which is a primary factor in the acceptance of AS-PSH into a utility’s generation mix. This CapEx will be greatly affected by the cost savings associated with the civil structure, turbine design, power electronics, control systems, or unique generator designs. A holistic design must be considered to get a full picture of the benefits of the technology proposed. The AS-PSH can be controlled to reduce the impact of transient disturbance on a power system and at the same time can be controlled to minimized subsequent component fatigue and potential oscillation modes within the plant, with the overall impact in reducing the operational expenditures (OpEx).Generating clean power to meet standards such as Institute of Electrical and Electronics Engineers (IEEE) 519 and International Electrotechnical Commission (IEC) 1000-3-2 will be a continuing challenge. For many technology developers, however, improved AS-PSH technologies will become a key component of generator-storage systems of the future given the prospects of increased performance and decreasing costs, and the ever-increasing penetration of renewables (e.g wind power and solar power).

13 HYDRO ENERGY↗
DOE OSTI2024

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Self-Healing Lithium Dendrites through Spontaneous Passivating Layer Formation for Stable Solid-State Lithium–Metal Batteries

All-solid-state lithium–metal batteries have attracted significant attention, owing to their high energy density and superior safety. However, lithium–metal penetration through the solid electrolyte, leading to short-circuiting, remains a critical failure mode that demands comprehensive mitigation strategies. Most existing strategies are effective only prior to the initiation of lithium-dendrite formation and fail once dendrites begin to propagate through the electrolyte. In this study, we propose a self-healing mechanism in which the penetrated lithium reacts with a self-healing agent to form a passivating layer along the particle boundaries. Lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) was incorporated into a Li 6 PS 5 Cl solid electrolyte as the self-healing agent to suppress lithium-dendrite propagation even after dendrite formation initiated under high current densities. The self-healing induced by LiTFSI was verified through comprehensive experimental analyses and was further demonstrated in a full-cell configuration. Moreover, LiTFSI incorporation plays an important role in increasing the critical current density by reducing the overall electronic conductivity of the solid electrolyte and facilitating the formation of a robust LiF-containing solid-electrolyte interphase.

25 ENERGY STORAGE↗
DOE OSTI2025

Exploring Micro-Environmental Conditions of Urban Agrivoltaics: Advancing Sustainable Green Spaces and Agriculture in Temperate Cities

Agrivoltaics, the integrated land use combining renewable energy production and agriculture, can potentially address key challenges faced by urban communities, including limited access to vacant land, fresh produce, and electricity. However, urban agrivoltaics has rarely been considered a viable solution, primarily due to a lack of experimental systems demonstrating the functionality of urban food production or green spaces alongside solar energy production. To evaluate the potential of solar photovoltaics to help mitigate heat stress on urban agriculture and green spaces in a temperate climate, we examined the microclimatic changes introduced by an urban agrivoltaics system (UrAV) when combined with vegetable crops and turfgrass, respectively. Accordingly, we installed an experimental setup instrumented with environmental sensors to compare full-sun conditions with those of an agrivoltaics system designed for urban environments. We found minimal differences for both land cover types between the control and agrivoltaics sites in air and soil temperature. However, during periods of intensified summer heat, temperatures beneath the panels cooled due to reductions in wind speed and relative humidity, which impeded the movement of hot, moist air and reduced reference evapotranspiration. Further, soil moisture in UrAV was highly spatially heterogeneous, influenced by the layout of the photovoltaic panels and their support structure, which redistributed rainfall and controlled where solar radiation could penetrate and drive evapotranspiration. Overall, our results suggest that PV-induced environmental changes in temperate climates are compatible with cultivating turfgrass or appropriate crops. These findings can help planners and designers integrate agrivoltaics into community gardens, farms, and green spaces in temperate cities.

14 SOLAR ENERGY↗
DOE OSTI2022

Chapter 2: Evaluating a Concentrating Solar Power Plantas an Extended-Duration Peaking Resource

We explore the ability of a concentrating solar power (CSP) plant with thermal energy storage (TES) to provide peaking capacity. We focus on future power systems, wherein net load patterns may be significantly different than they are today (e.g., due to higher renewable-energy penetrations). We examine 28 locations in the southwestern United States over an 18-year period. The hourly operation of the CSP plants are simulated to determine their potential to provide energy during an eight-hour peak-load window for each day up to 365 days per year. Our result shows that for the large majority of locations and years, CSP plants with certain configurations (i.e., in terms of solar field and TES sizes) can provide nearly 100% peak-load capacity. We examine also the amount of supplemental energy (e.g.,by using natural gas as a supplemental thermal-energy source) that would be required to ensure that a CSP plant could serve the eight highest-load hours of every day of the year. We find that in most cases, a CSP plant supplemented with natural gas would require less than 5% of the fuel that is used by a natural-gas fired power plant providing the same level of reliable capacity. A series of sensitivity analyses show that these results are robust to the number of peak-load hours and days that are considered and the configuration of the CSP plant.

capacity value↗
DOE OSTI2023

Evolution of Scenario Generation Capabilities in the ExaSGD Project

High-fidelity renewable energy scenarios and rare-event high-impact contingencies are essential for modeling operations and infrastructure expansion of the next generation power grids using exascale computing resources. As the ExaSGD project progressed, our capabilities for generating scenarios for modeling wind power output at multiple wind farms significantly improved, evolving from the use of independent random perturbations to importance sampling-based techniques capturing representative spatial-temporal relations. Contingency generation also improved, evolving from standard N-1 techniques to probabilistic models of infrastructure damage resulting from extreme weather events. We review the developments in the realistic intermittent-energy scenario forecasting and extreme-event contingency creation as the ExaSGD project progressed and discuss the future work in these areas.

economic dispatch↗
DOE OSTI2020

Electrical Energy Storage Data Submission Guidelines

Energy storage technologies are positioned to play a substantial role in power delivery systems. They are being touted as an effective new resource to maintain reliability and allow for increased penetration of renewable energy. However, due to their relative infancy, there is a lack of knowledge on how these resources truly operate over time. Data analysis can help ascertain the operational and performance characteristics of these emerging technologies. Rigorous testing and data analysis are important for all stakeholders to ensure a safe, reliable system that performs predictably on a macro level. Standardizing testing and analysis approaches to verifying the performance of energy storage devices, equipment, and systems when integrating them into the grid will improve the understanding and benefit of energy storage over time from technical and economic vantage points. Demonstrating the life-cycle value and capabilities of energy storage systems begins with the data the provider supplies for analysis. After review of energy storage data received from several providers, it has become clear that some of these data are inconsistent and incomplete, raising the question of their efficacy for robust analysis. This report reviews and proposes general guidelines such as sampling rates and data points that providers must supply for robust data analysis to take place. Consistent guidelines are the basis of the proper protocol and ensuing standards to (a) reduce the time it takes data to reach those who are providing analysis; (b) allow them to better understand the energy storage installations; and (c) enable them to provide high-quality analysis of the installations. This report is intended to serve as a starting point for what data points should be provided when monitoring. As battery technologies continue to advance and the industry expands, this report will be updated to remain current.

25 ENERGY STORAGE↗