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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Renewable Energy Potential (reV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling

The Renewable Energy Potential (reV) model is a platform for detailed assessment of renewable energy (RE) resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP) and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for assessment of resource potential, technical potential and supply curves at varying levels of detail. The platform runs on NREL's High Performance Computing system, providing scalable and efficient performance from a single location all the way up to continental scales, for a single year or decades of time series resource data. Coupled with NREL's System Advisor Model (SAM), reV supports resource assessment from 5-minute to hourly temporal resolution and provides for analysis of long-term (i.e., year-on-year) variability of RE generation (e.g., interannual variability and exceedance probabilities). Technical potential is measured as a function of resource potential and limitations put on developable land area defined by the user. For example, the user can limit development by land ownership, terrain, land use/cover, and urban areas, as well as custom inputs. Technology, grid interconnection and operation costs, based on the latest market data and future projections, are also embedded in the model. The supply curve module is a spatial sorting algorithm based on plant siting, grid interconnection cost, and regional competition, which provides a geographically discrete estimate of levelized cost of electricity (LCOE) and supply (i.e., capacity) for specific renewable technologies. The reV model currently provides broad coverage across North America, South and Central Asia, South America and South Africa to inform national- and international-scale analyses as well as regional infrastructure and deployment planning.

13 HYDRO ENERGY↗
DOE OSTI2025

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↗
DOE OSTI2022

Resilient, Rural, and Revolutionary: Salisbury Square's Direct-Current Affordable Microgrid Community: Preprint

The technology to interconnect buildings with a dedicated direct-current (DC) power distribution network is in place today; what is missing is a turnkey approach to designing a DC microgrid - and the business models allowing such systems to be deployed, owned, and operated at scale. To close this gap, the Salisbury Square Development Team, comprising clean-energy experts, has engineered a resilient community DC microgrid for an affordable housing community in Randolph, Vermont. Ten single-family, occupant-owned residences and 12 multifamily rental units will share locally generated and stored solar energy via a DC power distribution bus capable of operating during extended grid outages. With a DC power distribution network in place, each home will be equipped with high-efficiency DC lighting and appliances, operating alongside alternating current (AC) appliances, even during an islanded mode of operation. To obtain a comprehensive understanding of what is possible and achievable, the Team collaborated with the local utility, regulatory agencies, a national laboratory, energy-as-service providers, and vendors. The collaborators evaluated microgrid typologies, business models, and energy modeling, and analyzed electrification and resilience. Further, the Team applied the URBANoptTM (Urban Renewable Building and Neighborhood optimization, NREL 2022) software development kit (SDK) to Salisbury Square's single-family and multifamily buildings to validate workflows and identify needs for advanced capability. This paper addresses the barriers to entry, scalability, and impact on residents and system ownership. It also examines the analysis that informed the design and engineering of the DC microgrid and the opportunities to streamline the process.

DER↗
DOE OSTI2022

Driving Zn-MnO2 grid-scale batteries: A roadmap to cost-effective energy storage

Highlights Zn-MnO 2 batteries promise safe, reliable energy storage, and this roadmap outlines a combination of manufacturing strategies and technical innovations that could make this goal achievable. Approaches such as improved efficiency of manufacturing and increasing active material utilization will be important to getting costs as low as $100/kWh, but key materials innovations that facilitate the full 2-electron capacity utilization of MnO 2 , the use of high energy density 3D electrodes, and the promise of a separator-free battery with greater than 2V potential offer a route to batteries at $50/kWh or less. Abstract Large-scale energy storage is certain to play a significant, enabling role in the evolution of the emerging electrical grid. Battery-based storage, while not a dominant form of storage today, has opportunity to expand its utility through safe, reliable, and cost-effective technologies. Here, secondary Zn–MnO 2 batteries are highlighted as a promising extension of ubiquitous primary alkaline batteries, offering a safe, environmentally friendly chemistry in a scalable and practical energy dense technology. Importantly, there is a very realistic pathway to also making such batteries cost-effective at price points of $50/kWh or lower. By examining manufacturing examples at the Zn–MnO 2 battery manufacturer Urban Electric Power, a roadmap has been created to realize such low-cost systems. By focusing on manufacturing optimization through reduced materials waste, scalable manufacturing, and effective materials selection, costs can be significantly reduced. Ultimately, though, coupling these approaches with emerging research and development advances to enable full capacity active materials utilization and battery voltages greater than 2V are likely needed to drive costs below a target of $50/kWh. Reaching this commercially important goal, especially with a chemistry that is safe, well-known, and reliably effective stands to inject Zn–MnO 2 batteries in the storage landscape at a critical time in energy storage development and deployment. Graphical abstract

Spoerke, Erik D. (ORCID:0000000322862560)↗
DOE OSTI2021

The impact of development priorities on power system expansion planning in sub-Saharan Africa

Sub-Saharan Africa faces unique barriers to electricity development due to the large proportion of the population that is un-electrified and the prevalence of rural populations. Typically, power system expansion planning models assume all potential consumers can be immediately electrified. This assumption is unrealistic in sub-Saharan Africa, where electrification will likely be a gradual process over a number of years. Furthermore, since a large proportion of the population in sub-Saharan Africa is located in rural regions, the prioritization of these regions may impact how the grid develops. In this research, we develop a multi-period optimization model for power generation and transmission system expansion planning in sub-Saharan Africa. In contrast to existing models, which assume full electrification, we consider a variety of electrification policies and analyze the impact of varying the electrification rate and policy on the cost and resources selected for power system expansion. We test our model on a case study of Rwanda. We find that varying the year in which full electrification is reached has a larger impact on cost and generation capacity than varying the electrification policy does, although, when urban and rural regions are considered equitably, more rooftop solar is built. Varying the electrification policies has a larger impact on transmission expansion than on generation expansion and this impact is amplified when starting from zero initial system capacity rather than the original Rwanda system. Additionally, a sensitivity analysis shows that tightening the bounds on CO 2eq emissions has a large impact on the generation portfolio and cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Universal Battery Supercharger

During the course of the UBS project a dc-fast charger was developed to be used in off board high power charging stations. High efficiency is targeted to reduce the charging price for the consumer while reducing the charge time. In the meantime, the size of the converter is minimized so that it could be used in small spaces and potentially urban areas. The topology is modular, and the power level can be expanded for charging higher power vehicles like trucks and buses. During the course of this research several key technologies was developed in LESES that improve the performance of the power electronics system used in EV charger. Integrated magnetics was developed for DMCR to improve the power density as well as efficiency of the magnetic components which is one of the main bottlenecks of EV development. Triangular mode EV current conduction mode is using to perform soft switching (increase efficiency) without adding any new components to the existing topology. Passive and active damping are developed to suppress the interaction between grid and converter, stabilizing the control system. Further numerous other technical problems have been solved to pave the way for even higher performance converters in the future.

25 ENERGY STORAGE↗
NASA NTRS2014

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

Air pollution↗
DOE OSTI2022

The locational value of distributed energy resources: A parcel-level evaluation of solar and wind potential in New York state

We report distributed energy resources (DERs) are poised to play a significant role in evolving power systems because of their flexibility to be sited in areas of high value to the grid. Traditional DER compensation frameworks, specifically net energy metering (NEM), inadequately communicate differences in the locational and temporal value of DER generation to the grid. As a transition from NEM, New York State's (NYS's) Value of Distributed Energy Resources (VDER) framework provides a methodology for calculating different value components that DERs offer the grid. To study the impacts of VDER frameworks on DER deployment, we developed a model to assess the value of distributed solar and wind systems configured as either a behind-the-meter system or a front-of-the-meter system for each parcel of land in NYS. Using parcel-level granularity, we can closely evaluate DER locational value and siting availability, particularly in urban and suburban settings. Our analysis finds while most DER generators would be modestly compensated for deferred transmission and distribution infrastructure upgrades (~0.01 $\$$/kWh for solar PV), a subset of projects receive significant value from this component (0.035 to 0.089 $\$$/kWh for top 5% of parcels for solar PV). Finally, our analysis finds VDER provides less overall compensation than NEM to the average DER generator, however, it increases access to compensation for front-of-the-meter DERs - a large and emerging market.

14 SOLAR ENERGY↗
DOE OSTI2022

SEIN: Breaking Barriers Resilient Energy System Analysis [Slides]

The Solar Energy Innovation Network (SEIN) is a collaborative research program that supports multi-stakeholder teams in researching and sharing solutions to real-world challenges associated with solar energy adoption. The Breaking Barriers project was selected to participate in the Solar Energy Innovation Network, Round 2, and was led by Groundswell, a D.C.-based clean energy project developer. The Breaking Barriers team included Partnership for Southern Equity, Atlanta University Center campus facility managers and professors, the City of Atlanta's Neighborhood Planning Unit T, and Georgia Power Company. The project aimed to design and construct innovative urban energy resiliency hubs integrating microgrid technology, solar generation, and energy storage in Atlanta colleges and communities. The hubs will help these historically Black colleges and universities (HBCUs) and the energy-burdened broader community in West Atlanta be more resilient, in addition to informing new course curricula at Atlanta University Center campuses. With many possible options for the system's battery size, the Breaking Barriers team needed insight into the relationships between BESS size, economic performance, and resilience at Spelman College's Manley Center. These insights are crucial for entering procurement negotiations with project developers, establishing resilience capabilities that the HBCU campuses can plan around, and guiding the team's fundraising targets. This analysis includes estimates of PV and battery performance, costs, savings, and resilience for multiple battery sizes. In order to provide power during a grid outage, the resilient energy system also needs to be connected to the Manley Center in a safe and island-able manner (electrically isolated from the grid). Analysis of potential electrical configurations and estimated setup costs is key to successfully entering a required interconnection agreement with Georgia Power, as well as informing requests for engineering firms to construct the system. This analysis includes conceptual options and rough order of magnitude cost estimates for electrically interconnecting the resilient energy system to the Manley Center and the grid. The Breaking Barriers team used this analysis to select preferred system characteristics and design for the resilient energy system.

14 SOLAR ENERGY↗
DOE OSTI2020

Low-cost embedded optical sensing systems for distribution transformer monitoring

There is a mounting need for low-cost monitoring with online sensing technologies to maintain grid reliability and uptime. Here we introduce an innovative low-cost, embedded optical sensing technology initially focused on transformers that was developed and demonstrated at a major electric utility, Con Edison. A version of it that can be retrofitted onto existing transformers in the field was also developed. Two new 500 kVA distribution network transformers were built with embedded fiber-optic (FO) sensors and qualified per industry standards. Vibration, temperature, and corrosion were key parameters monitored. The first transformer with embedded FO sensors was installed at a Con Edison facility and monitored at our team’s office. The second one was installed in an urban street-side underground location with online data processing/feature extraction algorithms and monitored through a wireless router. Additionally, an older transformer was also retrofitted. Data analysis was done on these transformers showing promising correlations with their corresponding loading cycles. Furthermore, key events such as the transformer primary-side energizing, and other events were detected. In general, the technology was demonstrated over 6 months across the 3 transformers instrumented with promising results. Thus, it has the potential to enable predictive maintenance for transformers and other grid assets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Flexible Siting Criteria and Staff Minimization for Micro-Reactors

The economic potential of micro-reactors is vast and underestimated. Commonly-emphasized applications include niche markets such as remote communities, mines and military bases. However, micro-reactors could be used as flexible energy generators also for larger markets, such as mobile and containerized agriculture and manufacturing facilities, district heating, micro-grids for data centers, sea ports, airports and hospitals. The implication is that micro-reactors may have to be deployed also in non-remote locations. Successful implementation of micro-reactors needs a navigable and predictable licensing process, technology-appropriate siting restrictions, risk-informed emergency and safety requirements, and practical operating and maintenance requirements. The primary goal of this project was to develop siting criteria that are tailored to micro-reactors deployable in densely-populated areas, e.g., urban environments. To achieve that goal, we compared the characteristics of the MIT research reactor (MITR) with those of leading micro-reactor concepts (e.g., eVinci, USNC, Aurora), and evaluated whether and how the MITR design basis (e.g., inherent safety features, engineered safety systems, source term, emergency planning and emergency operating procedures) and associated regulations may be applicable to these new micro-reactors as well. What makes MITR a unique analogue in this context is its small power rating (6 MWt) and physical size, mode of operations (24/7 with a somewhat more commercial flavor than typical university reactors), and especially its urban location. Of course significant differences exist, such as mission (power production vs. research) and the reactor design itself. Leveraging the MITR experience, this project was able to generate criteria that will allow micro-reactors to realize their full economic potential as flexible heat and electricity generators for a diverse portfolio of applications in non-remote locations. As such, the outcome of this project might encourage investment in and use of micro-reactors. A second goal of the project was to conceptualize a model of operations for micro-reactors that would minimize the staffing requirements, and thus reduce the cost of electricity and heat generated by these systems. Here too our approach was to systematically review the MITR experience and requirements, as well as survey the innovations in autonomous control technologies and monitoring (e.g., advanced sensors, drones, robotics, AI) that would permit a dramatic reduction in staffing at future micro-reactor installations. The scope of work was expanded after the start date to include also an evaluation of micro-reactor security, using the so-called consequence-based analysis, and the development of a methodology to perform dynamic risk assessment for micro-reactors, using system theory and modeling and simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

TASTI-GRID: Improving Electric Grid Resilience across the State of Tennessee

Residential, industrial, and large load data center facility expansion have exacerbated management backlogs. Additionally, as newer technologies emerge in larger utility providers, a chasm between urban and rural resilience grows – creating segmentation across the state. With new development, industries, and large load additions to the electric grid across the Volunteer state, utilities must contend with these new connections, management backlogs, and technology gaps – while addressing an increase in major outages with more frequent extreme weather events, such as Hurricane Helene in 2024. This issues, in turn, have given way to greater vulnerabilities in adjacent infrastructure – including transportation and emergency management services, among others.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Sustainable urban transformations based on integrated microgrid designs

The impacts of natural hazards on infrastructure, enhanced by climate change, are increasingly more severe emphasizing the necessity of resilient energy grids. Microgrids, tailored energy systems for specific neighbourhoods and districts, play a pivotal role in sustaining energy supply during main grid outages. These solutions not only mitigate economic losses and well-being disruptions against escalating hazards but also enhance city resilience in alignment with Sustainable Development Goal (SDG) 11. However, disregarding socioeconomic factors in defining microgrid boundaries risks perpetuating inequalities and impeding progress towards other SDG 11 targets, including fair democratic participation. Our approach integrates social and technical indicators to bolster urban microgrid planning. Through a case study in a US county, we illustrate how integrated microgrid planning effectively intertwines urban resilience, well-being and equity while promoting sustainable development. This study underscores the importance of integrated microgrid planning for sustainable and resilient urban transformation amid environmental and societal challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Establishing nationwide power system vulnerability index across US counties using interpretable machine learning

Power outages have become increasingly frequent, intense, and prolonged in the US due to climate change, aging electrical grids, and rising energy demand. However, largely due to the absence of granular spatiotemporal outage data, we lack data-driven evidence and analytics-based metrics to quantify power system vulnerability. This limitation has hindered the ability to effectively evaluate and address vulnerability to power outages in US communities. Here, in this work, we collected ∼179 million power outage records at 15-min intervals across 3022 US contiguous counties (96.15 % of the area) from 2014 to 2023. We developed a power system vulnerability assessment framework based on three dimensions (intensity, frequency, and duration) and applied interpretable machine learning models (XGBoost and SHAP) to compute Power System Vulnerability Index (PSVI) at the county level. Our analysis reveals a consistent increase in power system vulnerability across the US counties over the past decade. We identified 318 counties across 45 states as hotspots for high power system vulnerability, particularly in the West Coast (California and Washington), the East Coast (Florida and the Northeast area), the Great Lakes megalopolis (Chicago-Detroit metropolitan areas), and the Gulf of Mexico (Texas). Our heterogeneity analysis indicates that urban counties and those located along regional transmission boundaries tend to exhibit significantly higher vulnerability. Our results highlight the significance of the proposed PSVI for evaluating the vulnerability of communities to power outages. The findings underscore the widespread and pervasive impact of power outages across the country and offer crucial insights to support infrastructure operators, policymakers, and emergency managers in formulating policies and programs aimed at enhancing the resilience of the US power infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

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↗
DOE OSTI2026

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

tell: a Python package to model future total electricity loads in the United States

The purpose of the Total ELectricity Load (tell) model is to generate 21st century profiles of hourly electricity load (demand) across the Conterminous United States (CONUS). tell loads reflect the impact of climate and socioeconomic change at a spatial and temporal resolution adequate for input to an electricity grid operations model. tell uses machine learning to develop profiles that are driven by projections of climate/meteorology and population. tell also harmonizes its results with United States (U.S.) state-level, annual projections from a national- to global-scale energy-economy model. This model accounts for a wide range of other factors affecting electricity demand, including technology change in the building sector, energy prices, and demand elasticities, which stems from model coupling with the U.S. version of the Global Change Analysis Model (GCAM-USA). tell was developed as part of the Integrated Multisector Multiscale Modeling (IM3) project. IM3 explores the vulnerability and resilience of interacting energy, water, land, and urban systems in response to compound stressors, such as climate trends, extreme events, population, urbanization, energy system transitions, and technology change

24 POWER TRANSMISSION AND DISTRIBUTION↗