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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

wmpy-power: A Python package for process-based regional hydropower simulation

Hydropower is an important source of renewable energy in many parts of the world. The generation potential for a hydropower facility can vary greatly due to fluctuations in precipitation and snowmelt patterns impacting streamflow and reservoir storage. Human activities such as irrigation, manufacturing, and hydration can also influence water availability at nearby and downstream facilities. wmpy-power--the hydropower model described in this work--is process-based, leveraging explicit reservoir storage and release data to address impacts on hydropower from climate change and human adaptive behaviors to inform long-term planning and resource-adequacy considerations.

13 HYDRO ENERGY↗
DOE OSTI2021

IDEAS-Watersheds FY21 Annual Report for July 1, 2020-June 30, 2021

Watersheds play a critical role in our water supply infrastructure and require sustainable management in a changing environment. Sustainable management of watershed systems and their interaction with the built environment rely on understanding the hydrologic and biogeochemical processes that control watershed system dynamics and water availability and quality. The overarching objective of the U.S. Department of Energy’s (DOE’s) Environmental System Science (ESS) program is to advance a robust, predictive understanding of how watersheds function and respond to perturbations as integrated hydrobiogeochemical systems. ESS supports a network of watershed testbeds within the United States where national laboratories and university partners work in interdisciplinary teams to advance watershed system science for energy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Development of a molecularly informed biogeochemical framework for reactive transport modeling of subsurface carbon inventories, transformations and fluxes (Final Report)

The overall objective of the project was to combine new molecular-level characterization strategies with soil carbon flux measurements to develop and evaluate model representations of subsurface carbon cycling. We expanded on existing studies in the East River watershed, Colorado, in collaboration with the Berkeley Lab Watershed Function Scientific Focus Area (SFA), SLAC Groundwater Quality SFA, and Rocky Mountain Biological Laboratory (RMBL) to develop an elevation and vegetation gradient that is now the subject of long-term monitoring by the USGS. To achieve the overall objective, we combined field studies of soil respiration with laboratory analyses, ranging from spectroscopy to incubation studies. This combination of techniques enabled us to develop a new understanding of the drivers of high-elevation soil respiration. In the process, we developed three new modeling approaches that improve our ability to conceptualize and ultimately to represent soil respiration in numerical models. The first approach is a plot-scale transient inverse model that can be used to determine in situ CO 2 production rates from measured concentration profiles and surface fluxes. Application of this method revealed the importance of plant phenology and deep CO 2 production in moderating CO 2 fluxes to the atmosphere. The second modeling approach is a molecular-scale tool that enables spectroscopic and elemental data for carbon speciation to be transformed into functional group abundances, or the ‘SOC-fga model’. This method uniquely enables carbon speciation to be tracked within a reactive transport framework to partition carbon among different pathways and storage zones within the soil. The third modeling tool builds strongly on the previous approaches and captures the microbial processes driving heterotrophic respiration. This ‘dormancy model’ allows the native soil microbial population to respond transiently to the presence or absence of water in order to catalyze carbon respiration. This approach was also compared to the simpler and more widely used first-order model using two experimental datasets with different temporal and spatial resolutions. Our results illustrate that the simpler first order model provides a robust and efficient representation of deep (>1 meter) soil respiration, but that shallow soils, where most respiration occurs, require explicit representation of moisture-dependent activation and dormancy rates. By assessing soil organic carbon turnover at multiple scales, we see a complex array of controls emerge. Atte scale of a hillslope, spatial heterogeneity in soil respiration rates dominates and is uncorrelated with instantaneous soil moisture and plant community. At the profile scale, the balance between plant inputs and water availability is the dominant control. At the microbial to molecular scale, physiological processes associated with carbon use and carbon speciation are important controls. These scale-dependent controls emphasize the need for new modeling approaches that examine their interactions and hierarchies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Comparison of the Neutronic Performance of IRP-1 and IRP-2 at SNS

The Spallation Neutron Source (SNS) operated from start-up, in May 2006, through December, 2017 before replacing the Inner Reflector Plug (IRP). This component is the most costly and time-consuming “regular maintenance” replacement foreseen in the operation of the First Target Station (FTS). The IRP includes beryllium reflector blocks, steel and aluminum support structures, aluminum moderator vessels (which in turn include gadolinium and cadmium neutron poisons) and water coolant systems. The lifetime of this multi-million dollar component is driven by poison and decoupler burnup in moderator vessels. The moderators include these neutron poisons to best match neutron beam performance with scattering instrument needs. The burnup that comes with use changes the performance of the moderators until they no longer server their intended purpose. The reasonable desire to maximize the IRP lifetime means that the moderator performance at the Beginning Of Life (BOL) is significantly “over poisoned” and different from the performance at moderator End Of Life (EOL). Upon installation of the second IRP article, IRP-2, the SNS Neutronics team characterized the performance of the neutron beamlines in order to assess the differences between them, primarily by comparing the EOL performance of IRP-1 to the BOL performance of IRP-2. While IRP-2 was largely similar to IRP-1 in its conceptual design, there were some differences in the specific design of IRP-2 to support enhanced manufacturability, and the change from IPR-1 to IRP-2 coincided with the replacement of the light water in the IRP cooling loop with heavy water, as had been intended in the SNS design but not implemented during construction because of heavy water availability.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Integrated Assessment Modeling of Grid Resilience: GCAM-to-PCM Scoping

Deep decarbonization towards a net-zero emissions future and the associated growth in power demand, renewables, and changes in water availability will require significant evolution in grid planning. Many obstacles threaten the viability of near-term generation capacity build out, including the need for large-scale transmission expansion. Current very-long term planning tools do not adequately model physical representations of economic dispatch and system topology down to inter- and intra-regional transmission and distribution infrastructure. This project attempts to fill that gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Microalgae Biomass Production for Utilization of CO2 and Mitigation of Greenhouse Gas Emissions

Microalgal cultivation processes for production of foods, feeds, fuels, fertilizers and other bioproducts and wastewater treatment are being considered for reducing CO2 and other greenhouse gas emissions. Major differences between microalgae and higher plant biomass cultivation are include their potential for much higher productivities, their higher content of major (N-P-K) and minor nutrients, and the challenge of harvesting such microscopic plants. Most critical, microalgal mass cultures, unlike higher plants, currently require fertilization with concentrated sources of CO2. As practically all of the C fixed into algal biomass will be re-emitted into the atmosphere in short order, algae processes do not sequester carbon. Their potential for CO2 emissions reductions must thus be based on comparisons with current technologies for the production of competing products, such as biofuels or animal feeds, or in wastewater treatment. Further, due to economic limitations to flue gas transport (3 to 12 % CO2), as well as highly variable diurnal and seasonal CO2 utilization and limited land and water availability near most CO2 sources, only a small fraction of waste CO2 emissions will be directly utilizeable for microalgae biomass production. However, for long-distance transport, flue gas CO2 capture by chemical processes would greatly increase the costs of flue gas utilization. More concentrated, sources of CO2 from refineries, fertilizer, chemical plants, and fermentations are available, but are also very limited relative to the quantities required for commodity production. Microalgae can also be cultivated on organic wastes, which provide both nutrients (N, P, K, etc.) and organic and inorganic carbon for algal growth, reducing greenhouse gas emissions compared to conventional treatment processes. To maximize the potential for algae biomass production and CO2 utilization, direct capture of CO2 from air will be required. This could be accomplished with the algal cultivation process itself in large open-raceway ponds, through chemical and biological enhancements of CO2 transfer into algal cutures. The relative productivities, economics, greenhouse gas balances, and resource potentials of these alternative CO2 sources for large-scale production of microalgae will be reviewed.

09 BIOMASS FUELS↗
DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗
DOE OSTI2025

Project-specific considerations for retrofitting carbon capture technology to power generating and industrial facilities

The National Energy Technology Laboratory (NETL) has previously reported on learnings from 7 FEED studies examining retrofitting power plants with capture. This presentation builds on this effort by highlighting learnings from 3 additional FEED studies examining retrofitting power plants with capture and 7 FEED and pre-FEED studies examining retrofitting industrial plants with capture. This includes a discussion of the design, performance, and cost implications associated with (1) site-specific considerations such as water availability, land availability, and site accessibility, and (2) host-plant-specific factors such as flue gas specifications, operational mode, and allowable degree of integration between the capture system and host plant.

FEED Studies↗
DOE OSTI2025

Existing Methods for Grid Strength Assessment and Role of Hydropower in Future Grids

The power system is undergoing rapid evolution with increasing penetration of inverter-based resources (IBRs), large loads, microgrids, and power electronic devices. Ensuring reliable and stable operation of the modern power grid is a multi-faceted challenge that requires detailed understanding of this complex system. Dynamic stability is a major concern in maintaining the security of power grids as the generation mixes and large loads transitions to include high shares of power electronic devices. The operation of IBRs in regions with low system strength and higher grid impedances has been found to be the main reason behind many of the power system instabilities that manifest themselves in various types of oscillations and interactions that, if not properly addressed and damped, can jeopardize the reliable operation of the power system. Weak grid conditions compound such stability problems, particularly when many IBRs operate in proximity to and connect to weak power grids. Therefore, it is important to assess grid strength for planning, integration and operation of IBRs for a given power system. In this report, we aim to understand and classify existing methodologies for grid strength assessment, along with their limitations and future needs. Further, we aim to utilize the huge untapped potential in utilizing hydro energy resources in addressing some of the pertinent challenges of grid strength and reliable operation of modern power systems. Hydropower, historically valued for its flexibility and dispatchability, now faces new constraints due to reduced share of synchronous machines in the generation mix and seasonal variability of available water resources. Yet, these same plants present untapped potential beyond energy generation - notably, as providers of critical grid services. This report explores how hydropower plants, particularly through operation as synchronous condensers, can play a pivotal role in strengthening the grid amid evolving system dynamics.

13 HYDRO ENERGY↗
DOE OSTI2020

Results for Voisin et al. 2020 [Data set]

These data files provide contemporary (2010) bulk electricity grid operations and transmission flow as simulated by PLEXOS and informed by historical and future generation constraints scenarios as informed by historical and future water availability at hydro and thermoelectric plants. Contact: Ana Dyreson , Nathalie Voisin Authors: Nathalie Voisin, Ana Dyreson, Tao Fu, Matt O'Connell, Sean Turner, Tian Zhou, Jordan Macknick

13 HYDRO ENERGY↗
DOE OSTI2024

Editorial: Advanced in situ characterization of biological interfaces and materials

Rapid changes are occurring on this dynamic planet–in 2020 anthropogenic mass was reported to not only match but exceed the mass of natural origins (Elhacham et al., 2020). These indications do not bold well for humanity in the coming generations, as we face 2 degree overall temperature increases over the next 5 years, CO 2 is spewing into the atmosphere at the Gigatonne (Gt) rate per year without any signs of mitigation in the foreseeable future, ocean water levels are rising to incredible levels, drinking water availability is disappearing, humanity is heavily reliant on the “drill-and-fill” culture, and two wars are currently being fought in Gaza and Ukraine (Carr et al., 2024). And even with these pressures, humanity continues to eke out impressive scientific and technological achievements in the recent past including mRNA vaccines to counter a global pandemic (Hogan and Pardi, 2022) and the development of CRISPR-Cas9 drugs (Parums, 2024). All these developments are only possible from the incremental methodological improvements taking place presently.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Trends and future outlooks in circularity of desalination membrane materials

Reverse osmosis desalination is one of the most important and increasingly popular technologies to augment available water resources. Central to the technology is a thin-film-composite polyamide membrane capable of separating pure water from seawater or brine. Since its conception and initiation, the membrane industry has followed a linear life-cycle scheme. However, increasing production costs of fossil-based materials and more stringent environmental regulations drive the initiatives to adapt to a circular economy of membrane materials. In this perspective, we briefly summarize the pressing issues in the state-of-the-art membrane industry, then discuss the opportunities in future technology innovations with a focus on sustainable membrane manufacturing and recycling, and lastly provided an outlook for future membrane design and fabrication towards a circular economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Next-Generation Intensity-Duration-Frequency Curves for Climate-Resilient Infrastructure Design: Advances and Opportunities

National and international security communities (e.g., U.S. Department of Defense) have shown increasing attention for innovating critical infrastructure and installations due to recurring high-profile flooding events in recent years. The standard infrastructure design approach relies on local precipitation-based intensity-duration-frequency (PREC-IDF) curves that do not account for snow process and assume stationary climate, leading to high failure risk and increased maintenance costs. This paper reviews the recently developed next-generation IDF (NG-IDF) curves that explicitly account for the mechanisms of extreme water available for runoff including rainfall, snowmelt, and rain-on-snow under nonstationary climate. The NG-IDF curve is an enhancement to the PREC-IDF curve and provides a consistent design approach across rain- to snow-dominated regions, which can benefit engineers and planners responsible for designing climate-resilient facilities, federal emergency agencies responsible for the flood insurance program, and local jurisdictions responsible for developing design manuals and approving subsequent infrastructure designs. Further, we discuss the recent advances in climate and hydrologic science communities that have not been translated into actional information in the engineering community. To bridge the gap, we advocate that building climate-resilient infrastructure goes beyond the traditional local design scale where engineers rely on recipe-based methods only; the future hydrologic design is a multi-scale problem and requires closer collaboration between climate scientists, hydrologists, and civil engineers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Editorial: Linking Hydrological and Biogeochemical Processes in Riparian Corridors

The riparian corridor is a key component of the critical zone and an essential component of watershed systems. According to Merriam-Webster Dictionary, the word riparian is derived from the Latin word riparius, meaning “existing alongside a river.” Riparian corridors typically extend from a few meters to hundreds of meters adjacent to a river and are marked by rich biodiversity, vegetation, and intense biogeochemical activity. They act as integrators of watershed processes and constitute the primary pathways for the subsurface geochemical exports from the watershed. Although riparian corridors comprise only 2–10% of a watershed's area, as much as 90–98% of biogeochemical processing in watersheds occurs in this region, thereby affecting the subsurface geochemical exports and downstream river water quality. Indeed, the riparian corridor is a good example of the Pareto principle. This outsized contribution occurs at the interface between aquatic (river) and terrestrial (land) environments, where interactions between hydrologic and biogeochemical processes are intensified. Variations in the river corridor over time can thus also have outsize impacts. Therefore, it is important to understand the hydrological and biogeochemical linkages in riparian corridors to determine water availability and quality for sustainable management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Fusion of Geothermal and InSAR Data with Machine Learning for Enhanced Deformation Forecasting at the Geysers

The Geysers geothermal field in California is experiencing land subsidence due to the seismic and geothermal activities taking place. This poses a risk not only to the underlying infrastructure but also to the groundwater level which would reduce the water availability for the local community. Because of this, it is crucial to monitor and assess the surface deformation occurring and adjust geothermal operations accordingly. In this study, we examine the correlation between the geothermal injection and production rates as well as the seismic activity in the area, and we show the high correlation between the injection rate and the number of earthquakes. This motivates the use of this data in a machine learning model that would predict future deformation maps. First, we build a model that uses interferometric synthetic aperture radar (InSAR) images that have been processed and turned into a deformation time series using LiCSBAS, an open-source InSAR time series package, and evaluate the performance against a linear baseline model. The model includes both convolutional neural network (CNN) layers as well as long short-term memory (LSTM) layers and is able to improve upon the baseline model based on a mean squared error metric. Then, after getting preprocessed, we incorporate the geothermal data by adding them as additional inputs to the model. This new model was able to outperform both the baseline and the previous version of the model that uses only InSAR data, motivating the use of machine learning models as well as geothermal data in assessing and predicting future deformation at The Geysers as part of hazard mitigation models which would then be used as fundamental tools for informed decision making when it comes to adjusting geothermal operations.

Yazbeck, Joe (ORCID:0000000302235260)↗
DOE OSTI2023

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗