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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. Here, this study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

A path-dependent fatigue crack propagation model under non-proportional modes I and III loading conditions

It has been well established that fatigue damage process is load-path dependent under non-proportional multi-axial loading conditions. Most of studies to date have been focusing on interpretation of S-N based test data by constructing a path-dependent fatigue damage model. Our paper presents a two-parameter mixed-mode fatigue crack growth model which takes into account of crack growth dependency on both load path traversed and a maximum effective stress intensity attained in a stress intensity factor plane (e.g.,KI-KIII plane). Furthermore, by taking advantage of a path-dependent maximum range (PDMR) cycle definition (Dong et al., 2010; Wei and Dong, 2010), the two parameters are formulated by introducing a moment of load path (MLP) based equivalent stress intensity factor range (ΔKNP) and a maximum effective stress intensity parameter KMax incorporating an interaction term KI·KIII. To examine the effectiveness of the proposed model, two sets of crack growth rate test data are considered. The first set is obtained as a part of this study using 304 stainless steel disk specimens subjected to three combined non-proportional modes I and III loading conditions (i.e., with a phase angle of 0°, 90°, and 180°). The second set was obtained by Feng et al. (2007) using 1070 steel disk specimens subjected to similar types of non-proportional mixed-mode conditions. Once the proposed two-parameter non-proportional mixed-mode crack growth model is used, it is shown that a good correlation can be achieved for both sets of the crack growth rate test data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Modeling of Inductive Constant Power Load for Electromagnetic-Transient Simulations-Part II

This paper improves the dynamic constant power (CP) load model that was published in Part I, which is appropriate for electromagnetic-transient (EMT). The improved model conserves all features of its predecessor. For instance, it maintains a fixed power consumption (both active and reactive parts) and a fixed power factor for loads that are predominantly inductive. Furthermore, as the proposed model is a time-dependent system, it is applicable to both sinusoidal and non-sinusoidal case studies. However, the previous model cannot be easily integrated with numeric solvers because it simulated load data over one cycle all together, not sequentially in a time-step manner, due to the limitation involved with the power factor. The improved version, on the contrary, allows the load to be simulated at every time step, which would facilitate its integration with numeric solvers. The model's validity is confirmed by comparing its response with data that is synthesized from constant impedance load, and the result is satisfactory.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Continuous Under-Frequency Load Shedding Scheme for Power System Adaptive Frequency Control

Frequency drop due to loss of massive generation is a threat to power system frequency stability. Under-frequency load shedding (UFLS) is the principal measure to prevent successive frequency declination and blackouts. Based on traditional stage-by-stage UFLS scheme, a new continuous UFLS scheme is proposed in this paper to shed loads proportional to frequency deviation. The characteristic of the proposed scheme is analyzed with a closed-form solution of frequency dynamics. Frequency threshold and time delay are added to make the proposed scheme practical. A line-by-line scheme based on precise load control is introduced to implement the continuous scheme for systems without enough continuously controllable loads. The load shedding scale factor of the proposed scheme is tuned with an analytical method to achieve adaptability to different operating conditions. Furthermore, the adaptability of the proposed scheme is validated with 39-bus New England model and simplified Shandong Power Grid of China.

42 ENGINEERING↗
DOE OSTI2019

Efficient and Zero Net Energy-Ready Plug Loads

Plug loads are the devices plugged into common electrical outlets. Modern buildings contain hundreds of these devices which, together, are responsible for at least 25 percent of the energy use in California buildings. Energy consumed by plug loads is increasing because the “Internet of Things” is, to a great extent, the “Internet of Plug Loads.” This project developed technologies that will reduce the energy use of plug loads. Two crosscutting strategies were investigated in detail: (1) technologies to reduce standby power use to near zero, and (2) methods to increase the use of direct current (DC) as a power source. Two new approaches to reduce standby to near zero were developed and have potential applicability to a wide range of devices. Prototype DC appliances were developed to demonstrate energy savings by bypassing power supplies and avoiding other losses. Networks of DC-powered devices can save even more energy and provide other benefits, such as resiliency during power outages. A unique category of energy-using devices was identified that provide life safety, health, and security to building occupants. Their installation or use is dictated by building codes, health providers, insurance companies, and other entities—none of whom would ordinarily prioritize energy efficiency. In the case of ground fault circuit interrupts (GFCIs), savings of 80 percent appear possible, simply by adopting the most efficient designs. Home medical equipment, particularly oxygen concentrators, are a rising category of energy use where significant savings are possible. This report also reviews the codes, standards, and other policies that affect energy use of plug loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2025 Large Load Literature Review

This literature review catalogs more than 90 publications focused on large loads, and groups the documents and resources thematically into 12 categories, (listed below). The 2026 Large Load Literature Review and Data Sources summary reports are available here: https://emp.lbl.gov/publications/2026-large-load-literature-review -Load forecasting -Data sources -Reliability and resource adequacy -Large load interconnection -Demand flexibility -Generation -Co-location -Data center location/infrastructure -Large load tariffs -Policy options -Maps and tools -Design and operations

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Assessment of Wind Turbine Component Loads Under Yaw-Offset Conditions

Renewed interest in yaw control for wind turbine and power plants for wake redirection and load mitigation demands a clear understanding of the effects of running with skewed inflow. In this paper, we investigate the physics of yawed operations, building up the complexity from a simplified analytical treatment to more complex aeroelastic simulations. Results in terms of damage equivalent loads (DELs) and extreme loads under operating, misaligned conditions are compared to data collected from an instrumented, utility-scale wind turbine. The analysis shows that multiple factors are responsible for the DELs of the various components, and that airfoil aerodynamics, elastic characteristics of the rotor, and turbulence intensities are the primary drivers. Both fatigue and extreme loads are observed to have relatively complex trends with yaw offsets, which can change depending on the wind-speed regime. As a result, good agreement is found between predicted and measured trends for both fatigue and ultimate loads.

17 WIND ENERGY↗
DOE OSTI2019

Sensitivity of Uncertainty in Wind Characteristics and Wind Turbine Properties on Wind Turbine Extreme and Fatigue Loads

Wind turbine design relies on the ability to accurately predict turbine ultimate and fatigue loads. The loads analysis process requires precise knowledge of the expected wind-inflow conditions as well as turbine structural and aerodynamic properties. However, uncertainty in most parameters is inevitable. It is therefore important to understand the impact such uncertainties have on the resulting loads. The goal of this work is to assess which input parameters have the greatest influence on turbine power, fatigue loads, and ultimate loads during normal turbine operation. An Elementary Effects (EE) sensitivity analysis is performed to identify the most sensitive parameters. Separate case studies are performed on (1) wind-inflow conditions and (2) turbine structural and aerodynamic properties, both using the National Renewable Energy Laboratory (NREL) 5-MW baseline wind turbine. The focus is on individual parameter sensitivity, though interactions between parameters are considered.

17 WIND ENERGY↗
DOE OSTI2015

Building America Case Study: Calculating Design Heating Loads for Superinsulated Buildings, Ithaca, New York; Technology Solutions for New and Existing Homes, Energy Efficiency & Renewable Energy (EERE)

Designing a superinsulated home has many benefits including improved comfort, reduced exterior noise penetration, lower energy bills, and the ability to withstand power and fuel outages under much more comfortable conditions than a typical home. Extremely low heating and cooling loads equate to much smaller HVAC equipment than conventionally required. Sizing the mechanical system to these much lower loads reduces first costs and the size of the distribution system needed. While these homes aren't necessarily constructed with excessive mass in the form of concrete floors and walls, the amount of insulation and the increase in the thickness of the building envelope can lead to a mass effect, resulting in the structures ability to store much more heat than a code built home. This results in a very low thermal inertia making the building much less sensitive to drastic temperature swings thereby decreasing the peak heating load demand. Alternative methods that take this inertia into account along with solar and internal gains result in smaller more appropriate design loads than those calculated using Manual J version 8. During the winter of 2013/2014, CARB monitored the energy use of three homes in climate zone 6 in an attempt to evaluate the accuracy of two different mechanical system sizing methods for low load homes. Based on the results, it is recommended that internal and solar gains be included and some credit for thermal inertia be used in sizing calculations for superinsulated homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Technology Solutions Case Study: Calculating Design Heating Loads for Superinsulated Buildings

Designing a superinsulated home has many benefits including improved comfort, reduced exterior noise penetration, lower energy bills, and the ability to withstand power and fuel outages under much more comfortable conditions than a typical home. Extremely low heating and cooling loads equate to much smaller HVAC equipment than conventionally required. Sizing the mechanical system to these much lower loads reduces first costs and the size of the distribution system needed. While these homes aren't necessarily constructed with excessive mass in the form of concrete floors and walls, the amount of insulation and the increase in the thickness of the building envelope can lead to a mass effect, resulting in the structures ability to store much more heat than a code built home. This results in a very low thermal inertia making the building much less sensitive to drastic temperature swings thereby decreasing the peak heating load demand. Alternative methods that take this inertia into account along with solar and internal gains result in smaller more appropriate design loads than those calculated using Manual J version 8. During the winter of 2013/2014, the Consortium for Advanced Residential Buildings team monitored the energy use of three homes in climate zone 6 in an attempt to evaluate the accuracy of two different mechanical system sizing methods for low load homes. Based on the results, it is recommended that internal and solar gains be included and some credit for thermal inertia be used in sizing calculations for superinsulated homes.

Building America↗
DOE OSTI2020

Considerations for Medium-Term Load Forecasting in Morocco

There are many factors that determine how demand for electricity may change over time. Medium-term load forecasting is a subset of load forecasting that focuses on the next year. This presentation summarizes analysis performed by NREL on medium-term load forecasting performed for the Moroccan energy system. This analysis includes hourly regressions and load clustering. This work also describes potential next steps that can be implemented by ONEE to improve this medium-term load forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Low-Load Space Conditioning Needs Assessment

Heating, ventilating, and air-conditioning (HVAC) equipment must be right-sized to ensure energy performance and comfort. With limited low-load options in the HVAC market, many new-construction housing units are being fitted with oversized equipment that creates system efficiency, comfort, and cost penalties. To bridge the gap between currently available HVAC equipment that is oversized or inefficient and the rising demand for low-load HVAC equipment in the marketplace, HVAC equipment manufacturers need to be fully aware of the needs of the multifamily building and attached single-family (duplex and townhouse) home market. Over the past decade, Steven Winter Associates, Inc. (SWA) has provided certification and consulting services for hundreds of housing projects and has accrued a large pool of data that describe multifamily and attached single-family home characteristics. The U.S. Department of Energy’s Building America research team Consortium for Advanced Residential Buildings (CARB) compiled and analyzed these data to outline the characteristics of low-load dwellings such as the heating and cooling design loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Investigation of high-speed shaft bearing loads in wind turbine gearboxes through dynamometer testing

Many wind turbine gearboxes require repair or replacement well before reaching the end of their design life. The most common failure is bearing axial cracks, commonly called white etching cracks (WECs), which typically occur in the inner raceways of the high-speed parallel-stage rolling element bearings. Although the root causes of WECs are debated, one theory is that they are related to routine dynamic operating conditions and occasional transient events prevalent in wind turbines that can result in high bearing stress and sliding of the rolling elements. Here, this paper examined wind turbine gearbox high-speed shaft bearing loads and stresses through modeling and full-scale dynamometer testing. Bearing outer race loads were directly measured and predicted using a variety of modeling tools in normal operations, misaligned conditions, and transient events particularly prone to bearing sliding. Test data and models of bearing loads were well correlated. Neither operational misalignment due to rotor moments nor static generator misalignment affected the bearing loads when compared with pure-torque conditions. Thus, it is not likely that generator misalignment is a causal factor of WECs. In contrast, during transient events, the bearings experienced alternating periods of high stress, torque reversals, and loads under the minimum requisite at high rotating speeds while showing indications of sliding, all of which could be related to the formation of WECs.

17 WIND ENERGY↗
DOE OSTI2022

Load shuffling during creep deformation of an additively manufactured AlCuMnZr alloy

Here, the high-temperature deformation behavior of an additively manufactured Al-Cu-Mn-Zr alloy is evaluated in the as-fabricated and heat-treated states using traditional ex-situ and in-situ neutron diffraction creep experiments performed at 300 °C. The dominant reinforcement phase in the alloy, θ-Al 2 Cu, despite its high volume fraction of ~10%, does not provide load transfer strengthening during creep deformation. Instead, the lattice strain evolution suggests a new mechanism we term “load shuffling” wherein the initial load is transferred away from precipitate-free zones along the grain boundaries where most of the θ-Al 2 Cu particles are located to precipitate-strengthened grain interiors. Notwithstanding the lack of load transfer strengthening, the as-fabricated AM Al-Cu-Mn-Zr alloy still possesses improved creep resistance at 300 °C relative to a cast alloy with similar composition. The proposed load shuffling mechanism explains the lack of observed L1 2 -Al 3 Zr strengthening at 300 °C and helps identify several strategies for improvement of elevated-temperature mechanical response of AM Al alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A meta-learning based distribution system load forecasting model selection framework

This paper presents a meta-learning based, automatic distribution system load forecasting model selection framework. Furthermore, the framework includes the following processes: feature extraction, candidate model preparation and labeling, offline training, and online model recommendation. Using load forecasting needs and data characteristics as input features, multiple metalearners are used to rank the candidate load forecast models based on their forecasting accuracy. Then, a scoring-voting mechanism is proposed to weights recommendations from each meta-leaner and make the final recommendations. Heterogeneous load forecasting tasks with different temporal and technical requirements at different load aggregation levels are set up to train, validate, and test the performance of the proposed framework. Simulation results demonstrate that the performance of the meta-learning based approach is satisfactory in both seen and unseen forecasting tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2020

The good, the bad, and the ugly: Data-driven load profile discord identification in a large building portfolio

Reducing the overall energy consumption and associated greenhouse gas emissions in the building sector is essential for meeting our future sustainability goals. Recently, smart energy metering facilities have been deployed to enable monitoring of energy consumption data with hourly or subhourly temporal resolution. This unprecedented data collection has created various opportunities for advanced data analytics involving load profiles (e.g., building energy benchmarking programs, building-to-grid integration, and calibration of urban-scale energy models). These applications often need preprocessing steps to detect daily load profile discords, such as: 1) outliers due to system malfunctions (the bad) and 2) irregular energy consumption patterns, such as those resulting from holidays (the ugly) compared to normal consumption patterns (the good). However, current preprocessing methods predominantly focus on filtering using statistical threshold values, which fail to capture the contextual discords of daily profiles. In addition, discord detection algorithms in building research are often aimed at finding individual building-level discords, which are not suitable at a large scale. Thus, here, we develop a method for automated load profile discord identification (ALDI) in a large portfolio of buildings (more than 100 buildings). Specifically, ALDI 1) uses the matrix profile (MP) method to quantify the similarities of daily subsequences in time series meter data, 2) compares daily MP values with typical-day MP distributions using the Kolmogorov-Smirnov test, and 3) identifies daily load profile discords in a large building portfolio. We evaluate ALDI using the metering data of both an academic campus and a residential neighborhood. Our results demonstrate that ALDI efficiently discovers measurement errors by system malfunctions and low energy consumption days in the academic campus portfolio, and it detects unique load shape patterns likely driven by occupant behavior and extreme weather conditions in the residential neighborhood.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Long term load forecasting accuracy in electric utility integrated resource planning

Forecasts of electricity consumption and peak demand over time horizons of one or two decades are a key element in electric utilities’ meeting their core objective and obligation to ensure reliable and affordable electricity supplies for their customers while complying with a range of energy and environmental regulations and policies. These forecasts are an important input to integrated resource planning (IRP) processes involving utilities, regulators, and other stake-holders. Despite their importance, however, there has been little analysis of long term utility load forecasting accuracy. We conduct a retrospective analysis of long term load forecasts on twelve Western U. S. electric utilities in the mid-2000s to find that most overestimated both energy consumption and peak demand growth. A key reason for this was the use of assumptions that led to an overestimation of economic growth. We find that the complexity of forecast methods and the accuracy of these forecasts are mildly correlated. In addition, sensitivity and risk analysis of load growth and its implications for capacity expansion were not well integrated with subsequent implementation. As a result, we review changes in the utilities load forecasting methods over the subsequent decade, and discuss the policy implications of long term load forecast inaccuracy and its underlying causes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗