Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ReEDS”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Metrics and Analytical Frameworks for Valuing Energy Efficiency and Distributed Energy Resources in the Built Environment: Preprint

This paper summarizes efforts to develop new—and enhance existing—analytical frameworks and metrics to quantify the value that grid-interactive efficient homes with solar (GEB-solar homes) can provide. Industry is working to characterize and understand these capabilities and benefits, but existing analytical frameworks for evaluating energy efficiency (EE) are often siloed from those that evaluate distributed energy resources (DERs). Five metrics were adapted from an extensive literature review and applied to case studies of a modeled home in Riverside, California: ramp up/down, cover factor demand/supply, and curtailable load. Eight different technology scenarios were analyzed using a more tightly connected suite of building-to-grid models (BEopt, REopt, ReEDS, and PLEXOS). Additionally, an initial version of the Cambium tool was developed, characterizing the marginal prices and emissions from NREL’s 2018 Standard Scenarios. These grid costs were extended to a time-varying proxy retail rate and applied as part of a new grid alignment metric. In the results, a more integrated combination of GEB-solar technologies led to a higher cover factor demand—the percentage of gross home load covered by on-site solar—however, a benchmark was required to determine what range of cover factor was “best” for given grid conditions. To that end, a grid alignment cost metric was applied to the case study scenarios. The average cost to serve the net load of the home decreased from a median of ~$0.24/kWh to ~$0.10/kWh when the most integrated technology scenario was optimized towards the grid pricing proxy versus the time-of-use (TOU) rate.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2022

Storage Futures Study: Grid Operational Impacts of Widespread Storage Deployment

This report, the fifth in the Storage Futures Study series, uses cost-driven scenarios from the ReEDS model as a starting point to examine the operational impacts of grid-scale storage deployment and relationships between this deployment and the contribution of variable renewable energy. We use commercial production cost modeling software to evaluate hourly operation of five scenarios that reach between 210 gigawatts (GW) and 930 GW of installed storage by 2050. We find that storage plays an important role in these power systems between now and 2050 - by storing the lowest-marginal cost generation (often, overgeneration from solar or wind plants) and generating energy during the highest net load periods of the day and year. Storage helps with the integration of variable renewable energy and by providing an important resource to provide continued reliable power.

battery↗
DOE OSTI2022

Emerging Trends in Power System Planning Models

This presentation highlights NREL's power system modeling capabilities, both existing and the future direction of improvements. Specific enhancements to the ReEDS (Regional Energy Deployment System) model and a new electricity market design testbed called EMIS (Electricity Markets and Investment Suite) were described. This content was part of a broader discussion to help inform the National Academies of Sciences, Engineering, and Medicine Committee on the Future of Electric Power in the U.S. on existing power system models and improvements needed in these models to capture the increasing complexity and interconnectedness of the power system.

capacity expansion modeling↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗
DOE OSTI2024

Evaluating Impacts of Sustainable Aviation Fuel Production with CO2-to-Fuels Technologies on High Renewable Share Power Grids

This paper investigates the impact of Sustainable Aviation Fuel production using CO2-to-Fuels technologies on a future power grid with a high share of renewable energy. We focus on understanding the implications of the 2050 SAF production goal on the U.S. power system's long-term planning, encompassing generation, transmission, and cost analysis. Via the Regional Energy Deployment System (ReEDS) model, we developed a detailed SAF electricity demand model based on a low-temperature electrolysis-syngas fermentation-ethanol pathway. Four SAF target scenarios which aims to meet 10%, 15%, 20%, and 27% of SAF demand by 2050. These scenarios are exhaustively simulated to assess their impact on the power grid. Our results reveal that increasing SAF demand will result in higher electricity requirements, as well as expanded generator and transmission capacities, leading to an overall rise in system costs. However, these impacts are manageable within the broader context of U.S. capacity expansion plans. This study provides valuable insights into incorporating the CO2-to-Fuels electricity demand model and other carbon capture technologies in power system planning, emphasizing their significance in shaping a sustainable energy future.

BIOMASS FUELS,POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Evaluating Impacts of Sustainable Aviation Fuel Production with CO2-to-Fuels Technologies on High Renewable Share Power Grid: Preprint

This paper investigates the impact of Sustainable Aviation Fuel (SAF) production using CO2-to-Fuels technologies on a future power grid with a high share of renewable energy. We focus on understanding the implications of the 2050 SAF production goal on the U.S. power system's long-term planning, encompassing generation, transmission, and cost analysis. Via the Regional Energy Deployment System (ReEDS) model, we developed a detailed SAF electricity demand model based on a low-temperature electrolysis-syngas fermentation-ethanol pathway. Four SAF target scenarios which aimto meet 10%, 15%, 20%, and 27% of SAF demand by 2050. These scenarios are exhaustively simulated to assess their impact on the power grid. Our results reveal that increasing SAF demand will result in higher electricity requirements, as well as expanded generator and transmission capacities, leading to an overall rise in system costs. However, these impacts are manageable within the broader context of U.S. capacity expansion plans. This study provides valuable insights into incorporating the CO2-to-Fuels electricity demand model and other carbon capture technologies into power system planning, emphasizing their significance in shaping a sustainable energy future.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗
DOE OSTI2025

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗
DOE OSTI2025

Assessing the Economic Value of Underground Thermal Storage for Hybrid Geothermal Power

Solutions are needed to address resource adequacy in the electric power system for highly decarbonized systems. The storage duration, the length of time a storage device can provide continuous output at its rated capacity, must be sufficient to receive full credit toward resource adequacy. Longer peaks and high fractions of variable renewable generation have increased the required duration to potentially seasonal durations. Underground Thermal Energy Storage (UTES) can be adapted to a hybrid storage power plant or heating and cooling applications to satisfy the need for long-duration storage. In this study, we use the Renewable Energy Deployment System (ReEDS) capacity expansion model to evaluate the increase in value for an enhanced geothermal system (EGS) resources by adding UTES. In modeled scenarios, using geothermal without storage as a baseline we compare the increase in economic value for plants with a range of storage characteristics. The added value of a hybrid storage plant changes depending on assumptions including the length of storage duration, efficiency, and ability to charge storage from the grid during periods of low energy prices. Relating proposed characteristics for geothermal UTES hybrids to the modeled economic value provides insight into economically viable costs for developing UTES as well as what combination of technology characteristics and future energy and policy assumptions drive significant value increases.

capacity expansion model↗
DOE OSTI2020

A Low-Cost Durable Na-FeCl2 Battery with Ultrahigh Rate Capability

Na-based batteries have long been regarded as an inexpensive, sustainable candidate for large-scale stationary energy storage applications. Unfortunately, the market penetration of conventional Na-NiCl2 batteries is approaching its limit for several reasons, including limited rate capability and high Ni cost. Herein, a Na-FeCl2 battery operating at 190 °C is reported that allows a capacity output of 116 mAh g-1 at an extremely high current density of 33.3 mA cm-2 (˜0.6C). The superior rate performance is rooted in the intrinsically fast kinetics of the Fe/Fe2+ redox reaction. Furthermore, it is demonstrated that a small amount of Ni additive (10 mol%) effectively mitigates capacity fading of the Fe/NaCl cathode caused by Fe particle pulverization during long-term cycling. The modified Fe/Ni cathode exhibits excellent cycling stability, maintaining a discharge energy density of over 295 Wh kg-1 for 200 cycles at 10 mA cm-2 (˜C/5).

Zhan, Xiaowen↗
DOE OSTI2020

A High-Performance Na-Al Battery Based on Reversible NaAlCl4 Catholyte

This work demonstrates a high-capacity and safe Na-Al battery pairing sodium metal anode and reversible NaAlCl4 catholyte for grid scale energy storage applications. The energy-rich sodium anode allows the full play of the aluminum cathode, resulting in a full-cell capacity of 308 mAh/g at a discharge voltage of 1.6 V. Benefiting from the use of ??-alumina solid electrolyte (BASE), molten sodium anode and reversible Al deposition/stripping from NaAlCl4 catholyte, the battery presents a stable Coulombic efficiency of 100% and energy efficiency of ~95%. At a rate of C/3 (6.77 mA/cm2), the cell maintains 282 mAh/g (447 Wh/kg) after 200 cycles with an excellent capacity retention of 97.6%. Moreover, we elucidate pathways to build sodium-anode-free cells from the discharged state under dry air, which further extends the feasibility of this battery for stationary storage applications. These findings are expected to provide a new platform for the development of practical Al batteries.

Zhan, Xiaowen↗
DOE OSTI2021

Vacancy‐Enabled O3 Phase Stabilization for Manganese‐Rich Layered Sodium Cathodes

Abstract Manganese‐rich layered oxide materials hold great potential as low‐cost and high‐capacity cathodes for Na‐ion batteries. However, they usually form a P2 phase and suffer from fast capacity fade. In this work, an O3 phase sodium cathode has been developed out of a Li and Mn‐rich layered material by leveraging the creation of transition metal (TM) and oxygen vacancies and the electrochemical exchange of Na and Li. The Mn‐rich layered cathode material remains primarily O3 phase during sodiation/desodiation and can have a full sodiation capacity of ca. 220 mAh g −1 . It delivers ca. 160 mAh g −1 specific capacity between 2–3.8 V with >86 % retention over 250 cycles. The TM and oxygen vacancies pre‐formed in the sodiated material enables a reversible migration of TMs from the TM layer to the tetrahedral sites in the Na layer upon de‐sodiation and sodiation. The migration creates metastable states, leading to increased kinetic barrier that prohibits a complete O3‐P3 phase transition.

Xiao, Biwei↗
DOE OSTI2019

Systems Metabolic Engineering of Escherichia coli Improves Coconversion of Lignocellulose-Derived Sugars

Currently, microbial conversion of lignocellulose-derived glucose and xylose to biofuels is hindered by the fact that most microbes (including Escherichia coli [E. coli], Saccharomyces cerevisiae, and Zymomonas mobilis) preferentially consume glucose first and consume xylose slowly after glucose is depleted in lignocellulosic hydrolysates. In this study, E. coli strains are developed that simultaneously utilize glucose and xylose in lignocellulosic biomass hydrolysate using genome-scale models and adaptive laboratory evolution. E. coli strains are designed and constructed that coutilize glucose and xylose and adaptively evolve them to improve glucose and xylose utilization. Whole-genome resequencing of the evolved strains find relevant mutations in metabolic and regulatory genes and the mutations’ involvement in sugar coutilization is investigated. The developed strains show significantly improved coconversion of sugars in lignocellulosic biomass hydrolysates and provide a promising platform for producing next-generation biofuels.

Kim, Joonhoon↗
DOE OSTI2020

Lightweight Software Process Improvement Using Productivity and Sustainability Improvement Planning (PSIP)

Productivity and Sustainability Improvement Planning (PSIP) is a lightweight, iterative workflow that allows software development teams to identify development bottlenecks and track progress to overcome them. In this paper, we present an overview of PSIP and how it compares to other software process improvement (SPI) methodologies, and provide two case studies that describe how the use of PSIP led to successful improvements in team effectiveness and efficiency.

Heroux, Michael A.↗