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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 OSTI2022

Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

Overview and Intended Use Cases: These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO). Scout benchmark scenario data are suitable for the following example use cases: setting high-level policy goals for the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050); exploring the effects of key dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market); determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions to 2050 under a given set of assumptions; and/or identifying the energy and emissions impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio. Scenario Summary: A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Automated Dynamic Demand Response Implementation on a Micro-grid

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2 R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2 R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability to dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2 R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.

Kuppannagari, Sanmukh R.↗
DOE OSTI2026

Bounding the costs of electric vehicle managed charging—supply curves for scenarios from 2025 to 2050

As electric vehicle (EV) adoption increases, the resulting EV battery charging will increase demand on the electric power grid. Through EV managed charging (EVMC) programs, charging can be shifted in time to support electric grid reliability and reduce electricity costs. EVMC can offer an alternative to additional supply-side generation, but the costs of EVMC implementation must be understood to evaluate the cost-benefits of EVMC. This paper presents bottom-up, forward-looking (from 2025 through 2050) estimates of the incremental costs associated with different EVMC dispatch mechanisms available to electric utilities. The costs of enabling EVMC for a range of customer participation levels are presented in the form of supply curves, which provide per-EV costs for a targeted level of participation. The largest drivers of cost variation are assumptions about future charging flexibility paradigms described in four scenarios. These supply curves can be used to quantify the expected costs of EVMC programs and enable comparison with supply-side or other demand flexibility alternatives.

25 ENERGY STORAGE↗
DOE OSTI2021

Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain

The food supply chain has experienced major disruptions from both demand and supply sides during the COVID-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer’s preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho’s potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is twofold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond COVID-19.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Loads as a Resource: Frequency Responsive Demand

Frequency control plays an important role in preserving the power balance of a multi-machine power system. Generators modify their power output when a non-zero frequency deviation is presented in order to restore power balance across the network. However, with plans for large-scale penetration of renewable energy resources, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive, but also technically difficult. Frequency control from the demand side or load control presents a novel and viable way for providing the desired frequency response. Loads can measure frequency locally and change their power consumption after a non-zero frequency deviation is presented in order to achieve power balance between generation and consumption. The specific objectives of this project are to: •Provide a framework to facilitate large-scale deployment of frequency responsive end-use devices •Systematically design decentralized frequency-based load control strategies for enhanced stability performance •Ensure applicability over wide range of operating conditions while accounting for unpredictable end-use behavior and physical device constraints •Test and validate control strategy using large-scale simulations and field demonstrations •Create a level-playing field for smart grid assets with conventional generators

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Framework for the Economic Analysis of Hybrid Systems Based on Exergy Consumption

Starting from an overview of the dynamic behavior of the electricity market the need of the introduction of energy users that will provide a damping capability to the system is derived as also a qualitative analysis of the impact of uncertainty, both in the demand and supply side, is performed. Then it follows an introduction to the investment analysis methodologies based on the discounting of the cash flow, and then work concludes with the illustration and application of the exergonomic principles to provide a sound methodology for the cost accounting of the plant components to be used in the cash flow analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PR100: Estimated Medium- and Heavy-Duty Electric Vehicle Adoption and Load Estimation in Puerto Rico through 2050

The 2-year Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study analyzed stakeholder-driven pathways to Puerto Rico’s clean energy future. Outputs relating to electricity demand modeling were partially informed by estimates of electric vehicle adoption across all classes of medium- and heavy-duty vehicles (MHDVs), and the ensuing charging loads. To create these estimates, the team developed a transportation model for MHDVs in Puerto Rico to estimate the amount and geospatial distribution of energy used. Charging schedules for the different end uses of MHDVs were then used to construct electric load shapes assuming a portion of those vehicles would be replaced by battery electric counterparts. Study results showed that, by 2050, electric vehicles may constitute roughly 50% of the MHDV population in Puerto Rico. The resulting electrical demand curve attributable to MHDV charging showed that, for solar energy-based electrical systems with limited energy storage, this demand may create challenges unless appropriately managed either on the demand or supply side.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Utility Sector Impacts of Reduced Electricity Demand

This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Powering Post-COVID-19 Resilient Recovery with Green Stimulus

As the coronavirus disease (COVID-19) pandemic spread globally in early 2020, many governments enacted lockdown measures as an initial containment response. These lockdowns, while effective in slowing infection rates, have also had substantial economic consequences. A series of supply and demand shocks, workforce and supply chain disruptions, and other impacts of the pandemic and ensuing lockdowns have upended the livelihoods for much of the world's population. This quick read spotlights how green stimulus plans and other recovery measures can support near-term recovery and enable longer-term power system resilience against future threats. The term “green stimulus” encompasses fiscal measures (i.e., governmental tax and spending actions) that support short-term economic activity that enhances environmental and natural resource quality over a longer term. The deployment of energy efficiency (EE) and renewable energy (RE) technologies, as well as associated initiatives (e.g., grid modernization, electrification of transport, and so on) have been demonstrably effective in providing this kind of short-run economic boost while simultaneously strengthening the resilience of the power sector. Along with green stimulus packages, concurrent action on the regulatory side—for example, the development of green building codes, updating grid interconnection standards, creating programs and marketplaces for demand-side efficiency, and others—can be a force multiplier in ensuring that public spending achieves maximum impact in near-term recovery and long-term power sector transformation

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Survey of U.S. Ancillary Services Markets

In addition to providing energy to end-consumers, power system operators are also responsible for ensuring system reliability. To this end, power markets maintain an array of ancillary services to ensure that it is always possible to balance the supply and demand for energy in real-time. A subset of these ancillary services are commonly procured through market-based mechanisms: namely, Regulation, Spinning, and Non-spinning Reserves. Regulation Reserves are maintained to respond to supply/demand imbalances over short time frames, typically on the order of several seconds to one minute. Resources that provide Regulation Reserves adjust their generation or load levels in response to automatic generation control (AGC) signals provided by the system operator. Contingency reserves are maintained to provide additional generation capacity in the event that load increases substantially or supply side resources reduce their output or are taken offline. The reserves are typically segmented into two categories, 1) Spinning or Synchronized Reserves that are provided by generation units that are actively generating and have the ability to increase or decrease their output, 2) Non-spinning or Non-synchronized Reserves that are provided by generation resources that are not actively generating, but are able to start up and provide generation within a specified timeframe. Contingency reserves typically have response times on the order of ten to 30 minutes and can also be provided by demand-side resources that are capable of reducing their load. There are seven distinct power markets in the United States, each operated by a Regional Transmission Operator (RTO) or Independent System Operator (ISO) that operates the transmission system in its territory, operates markets for energy and ancillary services, and maintains system reliability. Each power market offers its own set of ancillary services, and precise definitions, requirements, and market mechanisms differ between markets. Despite the differences between markets, both in terms of services offered and system requirements, some broad trends generally apply. Regulation Reserves typically have the highest market prices, followed by Spinning Reserves and Non-spinning Reserves. Prices for Regulation Reserves have been the highest in the PJM market, since it opened in October 2012. This is partially because PJM experienced large price spikes during the period of extreme weather conditions in early 2014. ERCOT has traditionally had the highest prices for Spinning Reserves (called Responsive Reserves in ERCOT), including several periods of sustained high prices between 2010 and 2012. This can be explained in part by the relatively high penetration of variable wind resources and a similarly high requirement relative to peak load. ERCOT has also traditionally had the highest price for Non-spinning Reserves, followed by the NYISO East region. Both have experienced several periods of prolonged high prices since their inception, an occurrence that has not been regularly seen in other markets. In ISO-NE and PJM for example, the market clearing price for Non-spinning Reserves is typically $0/MWh more than 95% of the time. Market volume (in terms of the average amount of capacity of each service that is provided to a system) typically follows the reverse order of prices, as systems maintain the most Non-spinning Reserves capacity followed by Spinning Reserves and Regulation Reserves. PJM generally has the largest market for Regulation Reserves both in terms of capacity. The size of most Regulation Reserves markets in terms of capacity stay relatively constant year-to-year, as this is dictated largely by system requirements. PJM also generally has the largest Spinning Reserves market in terms of capacity. SPP, MISO, ISO-NE and SPP (beginning in 2014) all have Spinning Reserve markets with similar average capacity levels. When combined, the markets for Non-spinning and Operating reserves in ISO-NE have a comparable capacity to the market for Primary Reserves 1 in PJM. SPP, MISO, and CAISO all have smaller markets for their respective Non-spinning Reserves products that are roughly the same size as each other in terms of capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Battery Electric Vehicle Driving and Charging Behavior Observed Early in The EV Project

As concern about society's dependence on petroleum-based transportation fuels increases, many see plug-in electric vehicles (PEV) as enablers to diversifying transportation energy sources. These vehicles, which include plug-in hybrid electric vehicles (PHEV), range-extended electric vehicles (EREV), and battery electric vehicles (BEV), draw some or all of their power from electricity stored in batteries, which are charged by the electric grid. In order for PEVs to be accepted by the mass market, electric charging infrastructure must also be deployed. Charging infrastructure must be safe, convenient, and financially sustainable. Additionally, electric utilities must be able to manage PEV charging demand on the electric grid. In the Fall of 2009, a large scale PEV infrastructure demonstration was launched to deploy an unprecedented number of PEVs and charging infrastructure. This demonstration, called The EV Project, is led by Electric Transportation Engineering Corporation (eTec) and funded by the U.S. Department of Energy. eTec is partnering with Nissan North America to deploy up to 4,700 Nissan Leaf BEVs and 11,210 charging units in five market areas in Arizona, California, Oregon, Tennessee, and Washington. With the assistance of the Idaho National Laboratory, eTec will collect and analyze data to characterize vehicle consumer driving and charging behavior, evaluate the effectiveness of charging infrastructure, and understand the impact of PEV charging on the electric grid. Trials of various revenue systems for commercial and public charging infrastructure will also be conducted. The ultimate goal of The EV Project is to capture lessons learned to enable the mass deployment of PEVs. This paper is the first in a series of papers documenting the progress and findings of The EV Project. This paper describes key research objectives of The EV Project and establishes the project background, including lessons learned from previous infrastructure deployment and PEV demonstrations. One such previous study was a PHEV demonstration conducted by the U.S. Department of Energy's Advanced Vehicle Testing Activity (AVTA), led by the Idaho National Laboratory (INL). AVTA's PHEV demonstration involved over 250 vehicles in the United States, Canada, and Finland. This paper summarizes driving and charging behavior observed in that demonstration, including the distribution of distance driven between charging events, charging frequency, and resulting proportion of operation charge depleting mode. Charging demand relative to time of day and day of the week will also be shown. Conclusions from the PHEV demonstration will be given which highlight the need for expanded analysis in The EV Project. For example, the AVTA PHEV demonstration showed that in the absence of controlled charging by the vehicle owner or electric utility, the majority of vehicles were charged in the evening hours, coincident with typical utility peak demand. Given this baseline, The EV Project will demonstrate the effects of consumer charge control and grid-side charge management on electricity demand. This paper will outline further analyses which will be performed by eTec and INL to documenting driving and charging behavior of vehicles operated in a infrastructure-rich environment.

25 ENERGY STORAGE↗
DOE OSTI2020

The sponge effect and carbon emission mitigation potentials of the global cement cycle

Cement plays a dual role in the global carbon cycle like a sponge: its massive production contributes significantly to present-day global anthropogenic CO 2 emissions, yet its hydrated products gradually reabsorb substantial amounts of atmospheric CO 2 (carbonation) in the future. The role of this sponge effect along the cement cycle (including production, use, and demolition) in carbon emissions mitigation, however, remains hitherto unexplored. Here, we quantify the effects of demand- and supply-side mitigation measures considering this material-energy-emissions-uptake nexus, finding that climate goals would be imperiled if the growth of cement stocks continues. Future reabsorption of CO 2 will be significant (~30% of cumulative CO 2 emissions from 2015 to 2100), but climate goal compliant net CO 2 emissions reduction along the global cement cycle will require both radical technology advancements (e.g., carbon capture and storage) and widespread deployment of material efficiency measures, which go beyond those envisaged in current technology roadmaps.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Geomatchd

Geomatchd is a software tool to assist non-experts in the rapid conceptual design of geothermal district heating systems. This tool comprises three main parts: user-side heating and cooling demand profiles, district heating and cooling (DHC) network models for sizing and optimal layout selection, and geothermal system models for heat extraction calculation and cost comparison. The architecture of Geomatchd is opensource and is intended to simplify efforts by other coders to improve on existing functions, to add functions and to leverage available existing code and data – to improve the tool for public use. Geomatchd and the material supporting its development may provide a more intuitive window on district heating and the use of local shallow geothermal resources.

AS↗
DOE OSTI2022

Direct and Sensitive Electrochemical Evaluation of Pramipexole Using Graphitic Carbon Nitride (gCN) Sensor

Pramipexole (PMXL) belongs to the benzothiazole class of aromatic compounds and is used in treating Parkinson’s disease; however, overdosage leads to some abnormal effects that could trigger severe side effects. Therefore, it demands a sensitive analytical tool for trace level detection. In this work, we successfully developed an electrochemical sensor for the trace level detection of PMXL, using the voltammetric method. For the analysis, graphitic carbon nitride (gCN) was opted and synthesized by using a high-temperature thermal condensation method. The synthesized nanoparticles were employed for surface characterization, using transmission electron microscopy (TEM), X-ray diffraction (XRD), and atomic force microscopy (AFM) techniques. The electrochemical characterization of the material was evaluated by using the electrochemical impedance spectroscopy (EIS) technique to evaluate the solution–electrode interface property. The cyclic voltammetry (CV) behavior of PMXL displayed an anodic peak in the forward scan, indicating that PMXL underwent electrooxidation, and an enhanced detection peak with lower detection potential was achieved for gCN-modified carbon paste electrode (gCN·CPE). The influence of different parameters on the electrochemical behavior was analyzed, revealing the diffusion governing the electrode process with an equal number of hydronium ions and electron involvement. For the fabricated gCN·CPE, good linearity range was noticed from 0.05 to 500 µM, and a lower detection limit (L D ) of 0.012 µM was achieved for the selected concentration range (0.5 to 30 µM). Selectivity of the electrode in PMXL detection was investigated by conducting an interference study, while the tablet sample analysis demonstrates the sensitive and real-time application of the electrode. The good recovery values for the analysis illustrate the efficiency of the electrode for PMXL analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Addressing Energy Demand through Demand Response. International Experiences and Practices

Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Optimal Load-Side Control for Frequency Regulation in Smart Grids

Frequency control rebalances supply and demand while maintaining the network state within operational margins. It is implemented using fast ramping reserves that are expensive and wasteful, and which are expected to become increasingly necessary with the current acceleration of renewable penetration. The most promising solution to this problem is the use of demand response, i.e., load participation in frequency control. Yet it is still unclear how to efficiently integrate load participation without introducing instabilities and violating operational constraints. In this paper, we present a comprehensive load-side frequency control mechanism that can maintain the grid within operational constraints. In particular, our controllers can rebalance supply and demand after disturbances, restore the frequency to its nominal value, and preserve interarea power flows. Furthermore, our controllers are distributed (unlike the currently implemented frequency control), can allocate load updates optimally, and can maintain line flows within thermal limits. We prove that such a distributed load-side control is globally asymptotically stable and robust to unknown load parameters. We illustrate its effectiveness through simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Consumer safety-oriented scheduling of rotating power outages during heat waves

Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.

Building thermal simulation↗