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At least 37 records · Page 2

A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data

With the expected increase in the number of electric vehicles (EVs) on the road in the coming years, it is important that analysis tools are capable of modeling and predicting the expected load on the power grid due to both individual EV charging sessions as well as large populations of vehicles. To do this accurately, the power profile of an EV charge session must be accurately modeled, including for scenarios where the temperature is above or below the ideal, and also take into account the nuances of manufacturer charging preferences. This paper introduces a method that utilizes the data in the Next-Gen Profile (NGP) data collection project to build a model of EV charging that takes into account the variations in charging power that occur due to off-nominal battery temperature and manufacturer preferences that limit power due to cold temperatures or high battery state-of-charge.

24 - POWER TRANSMISSION AND DISTRIBUTION

Myriad World Baseline: Global Geodemographic Estimates

The LandScan Myriad World Baseline (MWB) method produces global, residential (nighttime/home-location) gridded geodemographic estimates based on 5-year age/gender cohorts—at 30-arcsecond (≈1 km) resolution. MWB is designed to fill gaps where detailed, georeferenced survey data (e.g., Demographic and Health Surveys (DHS)) are missing or outdated, and to provide a baseline that can support human security analysis, including consequence assessment, “patterns of life” modeling, and scenario-based population futures. MWB’s workflow spatializes household-level age/gender characteristics from the GLOPOP-S dataset by conflating household and gridded expected relative wealth adapted from Global Gridded Relative Deprivation Index (GRDI), then adjusts them to a target year of interest. Age/gender estimates are then applied to harmonize lowest-administrative-level statistics with LandScan residential counts, yielding final geodemographic estimates. Two validation case studies are presented: Ghana (2021) and Tokyo/Kanagawa, Japan (2020), illustrating spatial variability in demographic cohorts and comparing MWB outputs to official gridded statistics. Results show close overall alignment relative to validation criteria including population pyramids and age-dependency ratios.

Tuccillo, Joe [ORNL] (ORCID:0000000259300943)

Preliminary Analysis of Nuclear-Powered Data Center Scenarios

This report provides a comprehensive analysis of the potential for nuclear energy to meet the growing energy demands of data centers (DCs). It evaluates the technical, economic, and socio-environmental implications of coupling Nuclear Power Plants (NPPs) with DCs, providing initial responses to several key research questions: What is the potential increased energy demand from DCs in the U.S., in the short, medium and long term? The U.S. is experiencing a rapid increase in energy demand from DCs, with projections indicating a total increase of 24-74 GWy(e) by 2028. Meeting this demand with nuclear energy would require 27–85 GWe of installed capacity. While this surge is expected to slow in the long term, the DC industry needs reliable, scalable, and clean energy sources. How much nuclear capacity can be deployed to meet DC demand and in which timeframe? Several pathways for increasing nuclear capacity were identified, including uprates, restarts of recently retired reactors, power purchase agreements with existing fleet, and new construction. Approximately 20‒28 GWe of nuclear capacity could be dedicated to DCs by the early 2030s. How much High Assay Low Enriched Uranium (HALEU) would be needed to support some nuclear deployment scenarios for DCs? Meeting the deployment targets announced by Google and Amazon for the Kairos Power Fluoride-Salt-Cooled High-Temperature Reactor or KP-FHR (~500 MWe by 2035) and the Xe-100 (~1 GWe by 2040), respectively, requires ramping up 19.75% enriched HALEU production to ~6 t/yr by 2040. What types of nuclear energy/DC coupling options exist, and what are the different benefits/challenges? Five coupling options were analyzed, ranging from grid-connected configurations to colocated, behind-the-meter setups. Key design considerations include the proximity to high- and/or medium-voltage transmission lines, the desired internal fault tolerance, and the sources of alternative/backup power during outages. Each coupling option offers unique benefits and challenges in terms of reliability, system costs, regulation, timeline, etc. A list of NPP/DC deployment scenarios was developed, considering existing or newly built NPP or DC projects. Colocated DCs with new small modular reactors or large reactors on greenfield and brownfield sites are the focus of this report. What types of reactors, especially what size, may be incentivized by DCs? Reactor sizing optimization revealed that the ideal reactor size and number of units depend on DC demand, coupling configurations defined in this report, and other economic factors. Larger reactors are preferred for high-demand DCs and grid-connected systems, while larger number of smaller reactors are better suited for DC configurations without grid backup. Which sites may be compatible with co-located nuclear-powered DCs? Siting those projects is a complicated evaluation factoring local water resources, grid connection availability and reliability, IT infrastructure, local work force, proximity to population zones, etc. For this effort greenfield and brownfield sites such as retired coal-fired plants were used to evaluate this question. This evaluation is not meant to recommend any particular site but it highlights key siting criteria and demonstrates large-scale site availability. What are the socio-economic impacts of co-located nuclear-powered DCs? Those projects generate substantial economic benefits to the local economy, particularly in urban settings. Hyperscale DCs colocated with nuclear power plants (sized around 1 GW of power) can create nearly 1,700 jobs for annual operations and more than 7,300 jobs among the supply chain and local businesses as a result of increased household spending. Rural projects also provide significant benefits, but at lower magnitudes compared to urban deployments.

22 GENERAL STUDIES OF NUCLEAR REACTORS

EV Load Forecasting Guide: A Report by the Energy Systems Integration Group’s EV Load Forecasting Task Force

Forecasting electricity usage is a foundational planning activity for utilities, underpinning billions of dollars in grid investments that ensure system reliability. Historically, forecasting relied on trends in economic and population growth; however, transportation electrification presents a new and complex planning challenge. Unlike conventional loads, electric vehicle (EV) charging has relatively limited usage history. In addition, charging is driven by complex human behaviors, is mobile, and at the same time can concentrate geographically in ways that, without proper planning, can quickly overwhelm local distribution systems.

Giraldez, Julieta [Electric Power Engineers, Austi

TASTI-GRID: An Overview of West Virginia’s Grid Resilience Challenges

West Virginia’s legacy as a top power producer with a legacy of mining and natural gas is well-known across the country. A state with historic underinvestment, vulnerability to natural hazards, and a large rural population – much of West Virginia’s critical energy infrastructure is beyond its recommended lifecycle at 75+ years old. West Virginian’s are feeling the effects of neighboring Virginia’s data center growth, as its grid interconnectedness with neighboring states have impacted energy affordability as power supply has not kept up with demand. The state aims to attract data centers to improve economic development, however, the age of infrastructure, utility reliability, weather-induced major outages, and cost of proposed improvements compound West Virginia’s resilience challenges.

24 POWER TRANSMISSION AND DISTRIBUTION

Total Effective Dose from Radiologic Emissions from INL Facilities for Calculation of Population Dose for the INL 2024 Annual Site Environmental Report

Total effective radiation dose from airborne releases was calculated using air dispersion modeling performed by the National Oceanic and Atmospheric Administration (NOAA) Idaho Falls Office using their HYSPLIT computer model (Stein et al. 2015; Draxler et al. 2013), and the Dose Multi-Media (DOSEMM) dose assessment model (Rood 2019) . The objective of these calculations was to provide a grid of total effective dose across a model domain that encompasses a 50-mile (80-km) radius from any Idaho National Laboratory (INL) Site source. In addition to INL Site sources, releases from the Radiological and Environmental Sciences Laboratory (RESL) (IF-683) and IF-603 located at the INL Research Center (IRC) within the Idaho Falls city limits were also included. Due to tracking limitations, radionuclides released from IF-611 and IF-603 are modeled as released from IF-603. The dose results will be combined with GIS software to compute a total population dose for the calendar year (CY) 2024 and will be reported in the INL Annual Site Environmental Report (ASER). This report does not cover the population dose calculation and only documents generation of the gridded dose file.

42 - ENGINEERING

Impact of truck electrification on air pollution disparities in the United States

Electrifying heavy-duty trucks reduces on-road diesel emissions but shifts the burden of supplying energy to power-generation facilities. The combined effect of Inflation Reduction Act investments in grid decarbonization and truck electrification will alter the magnitude and distribution of air pollution burdens across the United States. These investments are intended to facilitate a just energy transition, with 40% of the benefits flowing to disadvantaged communities per the Justice40 Initiative. Here we evaluate the combined effects of Inflation Reduction Act grid decarbonization and truck electrification investments on a national scale to determine whether the air pollution benefits would meet this 40% goal for both disadvantaged communities and the most exposed racial–ethnic groups. We find that truck electrification and decarbonization reduce air-pollution-related premature mortality in disadvantaged communities. However, the relative disparity between disadvantaged and non-disadvantaged communities increases, suggesting that a disproportionate share of benefits accrue to non-disadvantaged communities. Whereas absolute disparity in grid emissions decreases over time for all racial–ethnic groups, relative disparity remains largely unchanged, with Black populations being the most exposed. Electrifying drayage corridors would result in comparatively large health benefits for disadvantaged communities, suggesting that increasing targeted electrification investments in short-haul routes near urban areas (for example, ports) could be promising.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Scalable and Secure Power Outage Data Reporting: A Hexagonal Geospatial Approach

Power outages disrupt critical infrastructure and cause billions of dollars in economic losses annually in the United States. Accurate and granular outage reporting is vital for effective restoration and mitigation. This paper examines the integration of the Hexagonal Hierarchical Geospatial Indexing System (H3) to enhance power outage reporting, leveraging its uniform grid structure, scalable resolutions, and support for privacy-preserving analysis. Using high-resolution LandScan Global population data and K-anonymization techniques, this work achieves a balance between data granularity and privacy. Results show that lower privacy thresholds (e.g., K-anonymity = 2) enable higher resolution, while stricter thresholds (e.g., >15 people per hex) reduce granularity, potentially affecting localized responses. State-and county-level resolution case studies demonstrate H3’s adaptability and the trade-offs between precision and privacy. The proposed H3-based framework offers a scalable and efficient solution for geospatial data integration within the energy sector, such as outage data, aiding utilities and regulators in improving resilience and response efforts, particularly in disaster-prone regions.

Ahmad, Nasir [ORNL] (ORCID:0000000150677368)

Raccoon density estimation from camera traps for raccoon rabies management

Abstract Density estimation for unmarked animals is particularly challenging, yet density estimates are often necessary for effective wildlife management. Raccoons ( Procyon lotor ) are the primary terrestrial wildlife reservoir for Lyssavirus rabies within the United States. The raccoon rabies variant (RRVV) is actively managed at landscape scales using oral rabies vaccination (ORV) within the eastern United States. To effectively manage RRVV, it is important to know the density of raccoons to appropriately scale the density of ORV baits distributed on the landscape. We compared methods to estimate raccoon densities from camera‐trap data versus more intensive capture‐mark‐recapture (CMR) estimates across 2 land cover types (upland pine and bottomland hardwood) in the southeastern United States during 2019 and 2020. We evaluated the effect of alternative camera configurations and durations of camera trapping on density estimates and used an N‐mixture model to estimate raccoon densities, including covariates on abundance and detection. We further compared different methods of scaling camera‐based counts, with the maximum number of raccoons seen on any given image within a day best explaining density. Camera‐trap density estimates were moderately correlated with CMR estimates ( r = 0.56). However, densities from camera‐trap data were more reliable when classifying category of density as an index used to inform management (83% correct when compared to CMR estimates), although the densities in our study fell into the 2 lowest density classes only. Using more cameras reduced bias and uncertainty around density estimates; however, if ≤6 camera traps were used at a site, a line transect approach proved less biased than a grid design. Camera trapping should be conducted for at least 3 weeks for more accurate estimates of raccoon population density in our study area (<5% bias). We show that camera‐trap data can be used to assign raccoon densities to management‐relevant density index bins, but more studies are needed to ensure reliability across a greater range of environmental conditions and raccoon densities.

Davis, Amy J.

A Framework for Assessing Economic and Environmental Trade-offs of Internalized Emission Costs in ERCOT Grid Planning

The power grid is on the cusp of a massive transition driven by three major areas: 1) the growth in demand for electricity, 2) efforts to decarbonize the United States economy, and 3) a desire to mitigate social disparities from the impact of electricity generation on local populations. However, most studies of the electricity sector do not include equity impacts in their models. This study seeks to do so by developing a comprehensive and generalizable model tailored to the Electric Reliability Council of Texas (ERCOT) grid, designed to incorporate the equity impacts of electricity generation in a decarbonized and resilient framework. To integrate equity into our research, we incorporate environmental externalities into our capacity expansion model of ERCOT. Specifically, we factor in intermediate-level local marginal damages of precursor pollutants (NH3, NOx, primary PM2.5, SO2, and VOC) and global pollutant CO2 into the cost of generating electricity. We do this by taking into account county population, county ambient pollution concentration, and generator emission rates. Leveraging open-source modeling tools, such as PowerGenome, pyGRETA, and GenX we construct a county-level model to account for these costs. We integrate these marginal damages into the variable operations and maintenance costs of generators, for both existing and potential future builds. This study’s findings suggest that the value of a dynamic social cost of carbon (SSC) will cover criteria pollutant marginal damages within the ERCOT grid and solar and wind is expected to increase out to 2035. Key metrics evaluated within this research include fuel mix distribution across technologies, transmission and grid infrastructure costs, CO2 emissions, local pollutants marginal damages, and the variation in generation capacity built by the model. These results and framework can be used to support grid decisions that explicitly include distributional and procedural equity within a decarbonized and sustainable grid framework.

24 POWER TRANSMISSION AND DISTRIBUTION

Cybersecurity at the Grid Edge: Protecting LA's Energy Systems in a Connected World

Join SoCalGas and the National Laboratory of the Rockies (NLR) for an insightful webinar on securing operational technology and energy systems. Los Angeles has the second-largest metro by population in the nation, making it vital to protect the energy infrastructure that powers day-to-day life. However, cybersecurity for energy systems is an immense challenge due to an increasing number of interconnected devices and stakeholders. While there was traditionally a limited need to secure energy infrastructure, the grid is only becoming smarter and more software-defined. Amid aging infrastructure and evolving cyber threats, the need to ensure the security of energy is at an all-time high. Together, SoCalGas and NLR are assessing the current state-of-the-art of the energy ecosystem to understand gaps in current best practices and technologies relevant to powering the city of Los Angeles.

97 MATHEMATICS AND COMPUTING

Impacts of Alternative Operations and Renewable Energy Deployment on Columbia River Hydropower

The Columbia River Treaty Tribes in the Pacific Northwest - the Nez Perce, Umatilla, Warm Springs, and Yakama - hold treaty-reserved fishing rights for the Columbia River, one of the world's most productive salmon rivers and a critical resource for these tribes. However, the tribes have expressed that current operating regimes of hydropower dams throughout the Columbia River Basin (CRB) do not fully account for tribal fishing rights and have negatively impacted fish populations. Four tribes acting together through the Columbia River Inter-Tribal Fish Commission (CRITFC)'s 2022 Energy Vision stated that current power system models often do not fully account for the many constraints faced by hydropower facilities in the CRB. As the deployment of variable renewable energy (VRE) like solar and wind continues to increase, power system flexibility will become increasingly important. As a result, there is a growing need to better understand the true capabilities of the hydropower generation fleet while accurately accounting for ecological constraints (Northwest Power and Conservation Council 2022). Understanding hydropower's role in a future grid with a higher share of VRE can inform water resources planning to address ecological needs. The goal of this study is to examine the impacts of alternative hydropower operation rules and weather variability on hydropower generation and grid operations in VRE and transmission infrastructure deployment scenarios. The study evaluates how hydropower scheduling practices can reduce ecological impacts to the region's salmon populations. More specifically, the study examines the impact of today's dam water release rules (called "adjusted base water rules" in this study) and new, ecologically informed water release rules (called "ecosystem water rules" in this study) on two VRE scenarios (current renewable energy levels and higher renewable energy levels) using six weather years for each scenario (2008-2013). CRITFC developed the ecosystem water rules, which capture a portion of the changes they recommend for CRB hydropower operations. These analyses use a water resource planning model (OASIS) and a production cost model (PLEXOS) to simulate CRB reservoir cascade and Western Interconnection power grid operation.

13 HYDRO ENERGY

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River

Impact of Demographic Siting Criteria and Environmental Suitability on Land Availability for Nuclear Reactor Siting

The effect of population and certain environmental characteristics on the availability of land for siting nuclear power plants was assessed. The study area, consisting of the 48 contiguous states, was divided into 5 kilometer (km) square grid cells yielding a total of 600,000 cells. Through the use of a modern geographic information system, it was possible to provide a detailed analysis of a quite large area. Numerous maps and statistical tables were produced, the detail of which were limited only by available data. Evaluation issues included population density, restricted lands, seismic hardening, site preparation, water availability, and cost factors.

Hansen, K. L.

Updraft Width Modulates Ambient Atmospheric Controls on Convective Cloud Depth

Abstract The depth of convective clouds affects vertical transport of atmospheric constituents, influencing downstream weather and climate. Atmospheric controls on the maximum depth reached by moist convection are investigated with radar‐tracked convective cells tagged with sounding‐derived atmospheric parameters from a field campaign in central Argentina. Regression analyses show that narrow (<12‐km diameter) and wide (>16‐km diameter) cell depths respond to disparate factors, where cell areas are defined using composite reflectivity signatures. Undiluted lifted parcel indices including convective available potential energy (CAPE) and level of neutral buoyancy (LNB) are top predictors of wide cell maximum depth while mid‐tropospheric relative humidity is the top predictor of narrow cell maximum depth. Because narrow cells are more numerous than wide cells, the overall outcome of the full cell population does not strongly correlate with CAPE and LNB conditions. Tracked cells and atmospheric conditions in a simulation with 3‐km grid spacing covering the field campaign produce similar results to those observed. Narrow cells that are relatively deep have a cooler and moister mid‐troposphere with weaker free tropospheric subsidence, while relatively deep wide cells have much warmer and moister lower tropospheric conditions. These atmospheric differences are present 1 hr before cell initiation at both a fixed observing site and variable cell initiation locations. Simulated narrow cell maximum equivalent potential temperature decreases with height at a rate similar to the ambient vertical gradient, causing these cells to fall short of their LNB and supporting the view that entrainment‐driven dilution is a dominant control on their depth.

54 ENVIRONMENTAL SCIENCES

A North Carolina Retrospective: Major Outage Event Trends & Hurricane Helene using TASTI-GRID

The impacts of Hurricane Helene in September of 2024 showed magnifying effects on the number of major power outages reported both during and after the catastrophic weather event. The affected areas on the western edge of North Carolina, particularly Buncombe County (Asheville), endured a disproportionate number of outage impacts than surrounding counties atop the Piedmont Plateau. In 2024, each of the counties with the highest frequency of major outage events received at least one category of FEMA Disaster Declaration following Hurricane Helene. While the storm’s impacts certainly skewed 2024’s yearly major outage frequencies, we use TASTI-GRID to identify existence resilience challenges in the years prior to 2024 that may have given way to understanding how geography, topography, population density and other factors have compounding effects on existing resilience challenges in Buncombe and Mecklenburg counties, specifically.

24 POWER TRANSMISSION AND DISTRIBUTION

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.

Mongird, Kendall

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