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At least 19 records

Evaluating Recursive Blind Forecast Against API and Baseline: A Puerto Rican Case Study on Solar Irradiance for Normal and Extreme Weather

This paper leverages ongoing work in a community microgrid in Adjuntas, Puerto Rico to forecast global horizontal irradiance (GHI) and compare performance in normal and extreme weather. Given a positive correlation of 0.98 between GHI and PV power, forecasting GHI can be an effective, indirect forecast of photovoltaic (PV) power, especially in microgrids where the end-users, owners, operators, or other stakeholders are reluctant to share data for training or validation due to privacy and security concerns. A recursive one-shot (termed as "blind") forecast is, hence, formulated, wherein a gradient-boosted regression tree (GBR) is built to forecast GHI for a 7-day horizon in normal weather, and a 2-day horizon in extreme weather. To demonstrate its resilience, the architecture is trained on normal and hurricane weather GHI from 2002-2022. It is generalized on February 9-16, 2023, and on the landfall of Hurricane Nicole (Nov 4-5, 2022), respectively. Forecasts from GBR are compared against that from a satellite-based API resource and three baselines: persistence, averaging, and exponential smoothing. Results show GBR and persistence outperform sophisticated API in both types of weather for this case study.

Sundararajan, Aditya↗

A Weather Analysis for Xcel Energy's 2030 Colorado Preferred Plan

The Public Service Company of Colorado (PSCo), a subsidiary of Xcel Energy (Xcel), plans to meet its target of an 80% reduction in CO 2 emissions over 2005 levels by 2030 through its Preferred Plan1,2 that includes increasing the wind and solar energy on its system, reducing coal, and adjusting the operation and dispatch of new and existing thermal generation. The objective of our analysis reported here is to identify how the PSCo generation and transmission of its Preferred Plan might operate in the face of specific weather events. We investigate weather events that currently cause stress to PSCo’s system, such as winter storms and extreme heat. In addition, we explore how the future system responds to scenarios that may be considered normal weather conditions today, but that have a large impact on wind and solar generation potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

From models to reality: a systematic review on simulated and measured residential heat pump energy savings

High-performance HVAC solutions are central to residential energy management. A substantial share of these are electric, reversible-cycle systems, with heat pumps representing the largest portion of current and near-term adoption. This review synthesizes peer-reviewed and grey literature on residential space heating and cooling heat pumps. The academic literature is dominated by modeling (73.8%), with limited field measurement (13.1%). Grey literature from United States serve as a supplemental resource providing measured savings. Conversions from electric-resistance heating consistently show the largest site energy reductions, while oil/propane baselines yield moderate savings, and gas baseline scenario often deliver small and region-dependent savings. This study cross-checks the grey literature measured data with simulation data filtered from the ResStock dataset. The comparison indicates a discrepancy between simulations and measured data: simulated site EUIs are typically lower than measured EUIs, but percentage energy savings fall in similar ranges, implying simulations capture directional effects while underestimating energy use. Factors associated with variability and model–measurement differences include system characterization and control representation (e.g., backup heat engagement, thermostat/setpoint strategies, commissioning/installation quality), occupant behavior, weather normalization, metering scope, and envelope characterization. This paper also outlines the proposed methodology for comparing simulation and measured data for heat pumps. It emphasizes the metrics used for comparison and units harmonization, building characteristics matching, and compact metadata are needed for simulations to match measured data. The proposed methodology is expected to improve the credibility of simulated savings as measured evidence grows.

Yu, Lili↗

Customer outcomes in Pay-As-You-Save programs

We review the energy and financial outcomes of households participating in several programs based on successive versions of the Pay As You Save¯ (PAYS¯) system. PAYS¯ programs offer non-debt financing for energy efficiency (and sometimes other technologies) in residential buildings through a tariff attached to the home’s utility meter, designed to be offset by project savings. We find that the five programs we study generally serve customers living in zip codes with levels of income and education below the national average and unemployment rates above the national average, demonstrating their potential to improve equity in energy efficiency adoption. Using weather-normalized analysis of energy consumption data, we show that most customers of Midwest Energy’s program reduce annual electricity and gas consumption, averaging 15% and 26% reductions respectively. Changes in energy consumption calculated using this method represent a combination of project effects and changes in occupant behavior. These results are similar to existing analyses of PAYS¯ programs in North Carolina, Arkansas, and Tennessee. About half of participating Midwest households generate sufficient energy cost savings to cover their monthly tariff. Various factors, including changes in occupant behavior, program error, causes independent of the customer or program, or some combination thereof may explain lower-than-expected cost reductions in some projects. Given the inherent variability in annual household electricity consumption, we feel these programs are enabling energy efficiency improvements and their attendant co-benefits, including occupant health and comfort and reduced carbon emissions, while reasonably balancing energy savings and tariff costs. Pairing PAYS¯ with additional financial assistance, as well as promoting cost-effective measures such as air and duct sealing, could further broaden program participation by enabling additional projects to meet PAYS¯ program eligibility rules.

Deason, Jeff↗

A multi-level load shape clustering and disaggregation approach to characterize patterns of energy consumption behavior

This study presents representative electrical load shapes, disaggregated to the end-use level, for over 5000 customer clusters across California’s residential, commercial, industrial and agricultural sectors. We developed a novel, multi-level load shape clustering approach for residential and commercial sectors leveraging interval meter data for over 350,000 California utility customers collected as a part of the Phase 4 California Demand Response (DR) Potential Study. The clustering approach allowed us to identify typical consumption patterns and categorize customers based on their daily load shape displayed throughout the year. For example, we were able to identify customers with particular energy technologies such as electric vehicles and rooftop solar, as well as building occupancy types such as restaurants, grocery stores and even unoccupied buildings, based solely on whole-building interval data. We then combined the load shape-based clusters with other customer information including building type, climate, geographical area, total consumption and low-income status, to create a set of customer clusters based on both demographics and usage patterns. Total cluster electricity demand was then disaggregated into a wide variety of end-uses using weather normalization and other publicly available end-use load shape datasets. The resulting disaggregated cluster load shapes will be released in anonymized form as part of the Phase 4 DR Potential Study. They will have wide-ranging applications in energy research and policy analysis, including estimation of energy efficiency (EE) and DR potential on the end-use level, time-dependent valuation of EE savings, building stock modeling, and developing customer targeting strategies for EE and DR programs.

Murthy, Samanvitha↗

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗

2021 Summer Resource Adequacy in the ERCOT Region

This report is an update to the NETL report on the same topic that examined the potential system performance of the Electric Reliability Council of Texas (ERCOT) system during the summer of 2020. Anticipated reserve margins in ERCOT have risen year-over-year from the 10.7 percent reported in ERCOT’s Final Seasonal Assessment of Resource Adequacy (SARA) for Summer 2020 to 15.7 percent for Summer 2021 in ERCOT’s Capacity, Demand and Reserves [CDR] report published in December 2020 and 2021 Summer Preliminary SARA published in March 2021. Using data from ERCOT’s 2021 Summer SARA, CDR, and historical performance data, six economic dispatch scenarios using PROMOD were developed to assess the risk to ERCOT of a load shedding event for Summer 2021. The results suggest that ERCOT could make it through the summer season without a loss of load event, as long as the weather remains normal. However, through a combination of scenarios, including increased demand, increased forced outages, and low wind output, ERCOT is likely to find itself operating in emergency conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Global horizontal spectral irradiance in Albuquerque - Data and Resources

The Photovoltaic Systems Evaluation Laboratory (PSEL) at Sandia National Laboratories (SNL) in Albuquerque, NM has measured global horizontal spectral irradiance nearly continuously from September 2019 to March 2022. During this time other broadband irradiance measurements (global horizontal, direct normal, diffuse horizontal and global normal) and weather variables were also recorded. For this dataset PV Performance Labs (PVPL) has pulled together data from both sources to assemble a calendar year spectral data set for use in photovoltaic research. It is composed of twelve segments of 15 days each, beginning with January 1-15 and ending with December 1-15. The segments are all taken from the two-year period October 2019 to September 2021.

14 SOLAR ENERGY↗

Global normal spectral irradiance in Albuquerque - Data and Resources

The Photovoltaic Systems Evaluation Laboratory (PSEL) at Sandia National Laboratories (SNL) in Albuquerque, NM has measured global normal spectral irradiance nearly continuously from August 2013 to April 2018. During this time other broadband irradiance measurements (global horizontal, direct normal, diffuse horizontal and global normal) and weather variables were also recorded. For this dataset PV Performance Labs (PVPL) has pulled together data from both sources to assemble a full calendar year spectral data set for use in photovoltaic research. It is composed of eight continuous segments of different durations taken from the two-year period September 2013 to August 2015.

photovoltaics↗

Improving Residential Building Simulations Through Large-Scale Empirical Validation

Residential building energy simulations are increasingly used for energy-efficient building design, codes and standards analysis, home certifications and ratings, utility programs, and technology assessments. Various software tools exist to perform residential building simulations, and these tools often use different models, inputs, and assumptions. This leads to inconsistencies that can undermine confidence in the predicted results. Validation of these tools can increase confidence by ensuring their accuracy and consistency. One way to validate simulation tools is through empirical testing, which compares predicted energy usage to measured utility billing data. This paper describes the process of data collection, data standardization, and empirical validation, and illustrates its use with our residential EnergyPlus (R)-based software. The data and process can be extended to other simulation tools and contribute to improving residential building simulations more broadly.

empirical validation↗

Understanding Observed Precipitation Change and the New Climate Normal from the Perspective of Daily Weather Types in the Southeast United States

Abstract Observed precipitation changes in the Southeast United States (SEUS) are spatially heterogeneous. Most of the inland SEUS and eastern Gulf Coast become drier, and the East Coast north of Charleston, South Carolina, and southern Florida become wetter from the old 30-yr period of 1961–90 to the recent period of 1991–2020. The observed climate change is examined from the perspective of daily weather types (WTs). A k -means clustering analysis has been conducted using daily 850-hPa circulation for 1948–2021. The obtained 10 WTs peak in different seasons, respectively. The frequencies and precipitation intensity of the WTs have been analyzed. A winter WT characterized by a western Appalachian trough (WAT) and a summer WT featuring North Atlantic subtropical high (NASH) have a rising trend of annual frequency from 1948 to 2021. An Appalachian high in the autumn has a decreasing frequency but becomes drier and stronger. Some precipitation intensity change and small location shift have also been observed. The drying up on the eastern Gulf Coast and the inland area of the SEUS is mainly caused by the weakened southwesterly low-level jet (LLJ) on the western flank of the NASH that reduces rain in the spring, the less frequent but stronger and drier Appalachian high in the summer and autumn, and the weaker and more western located Plains trough (PT) in the winter, spring, and autumn. The precipitation increase in the East Coast and southern Florida is majorly due to more frequent, stronger, and rainier troughs along the western Appalachian as well as the East Coast.

Qian, Jian-Hua↗

An experimental study on round-trip efficiency of a preheating control with a medium office building

The interactions between building energy efficiency and demand response (DR) with buildings may complicate their impacts on the electricity grid and buildings, yet those interactions are not well understood. This work fills this gap by presenting an experimental study that quantifies the effects of DR on building energy efficiency. Unlike existing studies, this work 1) investigates the uncertainty levels when assessing the effects of DR; 2) studies the impact of rooftop heat pumps with direct expansion refrigerant-to-air coils on the round-trip efficiency. Specifically, we considered a medium office building (~1860 m 2 ), which is served by rooftop units, located in eastern Washington State. We performed preheating control tests during typical heating days in the year 2022 and compared the building’s energy consumption during the testing days to that during normal operation days under similar weather conditions. To understand how well those normal operation days represent the baseline for the assessment, the relationship between the energy performance of this building and weather conditions was also studied. Experimental results reveal that the round-trip efficiency (i.e., the ratio of discharging energy output from the building to charging energy input into the building) was between 0.16 and 0.92. The results show that significant energy loss may occur during the preheating process. Finally, it also suggests a significant correlation between the energy efficiency of the studied building under the preheating control and the outdoor temperature; and a highly nonlinear relationship between the zone temperature changing rate and the weather condition.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Experimental Plan for the Vermiculite Study

Homes in which vermiculite, which can contain asbestos, is present are often deferred under the DOE Weatherization Assistance Program (WAP) because of uncertainty in how to safely weatherize such homes from a client and worker perspective and the potential costs associated with alternative approaches. Recognizing this situation, the Department of Energy (DOE) tasked the Oak Ridge National Laboratory (ORNL) to perform a research project that scientifically identifies the asbestos exposure risks in weatherizing homes with existing vermiculite insulation. Current approaches being used by Grantees and Subgrantees to weatherize homes with existing vermiculite insulation were identified as part of the development of this experimental plan based on a review of Grantee Health and Safety Plans and communications with weatherization program staff from seven states. Other than deferral, these approaches include the following:1.) Abating (i.e., removing) the existing vermiculite using funding sources other than WAP (e.g., state funds, utility funds, the Zonolite Attic Insulation Trust Fund, and possibly homeowner contributions) because abatement is not allowed using WAP funds per Weatherization Program Notice (WPN) 17-7. 2.) Weatherizing the house as normal after testing reveals that the vermiculite contains less than 1% asbestos. 3.) Avoiding areas of the house where vermiculite is installed and weatherizing the remaining areas of the house as normal. 4.) Encapsulating the existing vermiculite insulation in an attic by blowing cellulose or other insulation over it. 5.) Weatherizing the areas of the house where vermiculite is installed using unique/alternative approaches developed specifically for that house. Blower door testing is also impacted by the presence of vermiculite due to the concern of bringing asbestos fibers into the space. Some states address this by performing pressurized blower door tests, whereas other states prohibit blower door testing entirely when vermiculite is present. This research project will focus on gathering data on home occupant and weatherization worker exposures to asbestos before, during, and/or after the weatherization of the homes containing vermiculite insulation using five of the six approaches identified above. Abatement of the existing vermiculite insulation will not be studied because it is not allowed using WAP funding per WPN 17-7 and, thus, is not a sustainable approach for WAP.

36 MATERIALS SCIENCE↗

Diabatic Eddy Forcing Increases Persistence and Opposes Propagation of the Southern Annular Mode in MERRA-2

Abstract As a dominant mode of jet variability on subseasonal time scales, the Southern Annular Mode (SAM) provides a window into how the atmosphere can produce internal oscillations on longer-than-synoptic time scales. While SAM’s existence can be explained by dry, purely barotropic theories, the time scale for its persistence and propagation is set by a lagged interaction between barotropic and baroclinic mechanisms, making the exact physical mechanisms challenging to identify and to simulate, even in latest generation models. By partitioning the eddy momentum flux convergence in MERRA-2 using an eddy–mean flow interaction framework, we demonstrate that diabatic processes (condensation and radiative heating) are the main contributors to SAM’s persistence in its stationary regime, as well as the key for preventing propagation in this regime. In SAM’s propagating regime, baroclinic and diabatic feedbacks also dominate the eddy–jet feedback. However, propagation is initiated by barotropic shifts in upper-level wave breaking and then sustained by a baroclinic response, leading to a roughly 60-day oscillation period. This barotropic propagation mechanism has been identified in dry, idealized models, but here we show evidence of this mechanism for the first time in reanalysis. The diabatic feedbacks on SAM are consistent with modulation of the storm-track latitude by SAM, altering the emission temperature and cloud cover over individual waves. Therefore, future attempts to improve the SAM time scale in models should focus on the storm-track location, as well as the roles of the cloud and moisture parameterizations. Significance Statement As they circumnavigate the planet, the tropospheric jet streams slowly drift north and south over about 30 days, longer than the normal limit of weather prediction. Understanding the source of this “memory” could improve our knowledge of how the atmosphere organizes itself and our ability to make long-term forecasts. Current theories have identified several possible internal atmospheric interactions responsible for this memory. Yet most of the theories for understanding the jets’ behavior assume that this behavior is only weakly influenced by atmospheric water vapor. We show that this assumption is not enough to understand jet persistence. Instead, clouds and precipitation are more important contributors in reanalysis data than internal “dry” mechanisms to this memory of the Southern Hemisphere jet.

54 ENVIRONMENTAL SCIENCES↗

Tracking the PACE of household energy usage: Energy usage impacts of projects financed through Property Assessed Clean Energy programs in California

This report examines the household-level energy impacts of residential property assessed clean energy (R-PACE) projects using normalized metered energy consumption methods. Our analysis covers projects that occurred through an R-PACE program between 2009 and 2017 and includes more than 25,000 electricity meters and 15,000 gas meters. We employ a comparison group, drawn from other R-PACE households with similar locational and usage characteristics whose projects were implemented at different times, to control for some non-project and non-weather factors that may impact energy use. We find that projects consisting of energy efficiency technologies save, on average, about 3% of household electricity usage and 3.5% of household gas usage. R-PACE financing, however, can be used to install central heating or air conditioning equipment for the first time. These projects would be expected to increase energy consumption. Since our data do not directly indicate which projects are new installations, we develop a simple algorithm for identifying them. Removing these inferred installation projects yields average savings of about 5% for electricity and 6% for gas for those households that remain in the sample. Given the mild California climate and the results of another study of similar California projects using similar methods, these results are in line with expectations. Solar PV projects yield large reductions in grid electricity use, averaging 69% of household consumption. We estimate that, collectively, all R-PACE projects installed in California through 2019 would generate annual reductions in grid-tied electricity consumption of 506 GWh (mostly due to solar PV) and gas consumption reductions of 2 million therms in a normal weather year. These impacts are equivalent to the electricity consumption of about 74,000 California households (including both efficiency and PV generation) and the gas consumption of about 4700 California households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Annual Solar Irradiance Anomaly Features Over the USA During 1998-2017 Using NSRDB V3

Annual solar irradiance anomalies (or departures from the long-term mean annual value) have a direct impact on various phases of solar energy projects, from prefeasibility studies to technical deployment decisions. Anomalies can happen because of normal climate variability or exceptional weather patterns. This study investigates such anomalies for both global horizontal irradiance (GHI) and direct normal irradiance (DNI) using Version 3 of the National Solar Radiation Database (NSRDB V3) and surface irradiance measurements at eight U.S. locations. At each site, the annual anomaly is analyzed here by evaluating the irradiance deviation from the long-term average for each specific year from 1998–2017. A positive/negative anomaly indicates that the solar resource was higher/lower than the long-term average during that specific year. The results show that in most cases the anomaly is within ±5% for GHI and ±10% for DNI using either ground-based irradiance measurements or modeled data from the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Annual Solar Irradiance Anomaly Features Over the USA During 1998-2017 Using NSRDB V3: Preprint

Annual solar irradiance anomalies (or departures from the long-term mean annual value) have a direct effect on various phases of solar energy projects, from prefeasibility to deploy-ment. Anomalies can happen because of normal climate varia-bility or exceptional weather patterns. This study investigates such anomalies for both global horizontal irradiance (GHI) and direct normal irradiance (DNI) using Version 3 of the National Solar Radiation Database (NSRDB V3) and surface irradiance measurements at eight U.S. locations. At each site, the annual anomaly is analyzed here by evaluating the irradi-ance deviation from the long-term average for each specific year during 1998–2017. A positive anomaly indicates that the solar resource was higher than the long-term average during that specific year, and vice versa in the case of a negative anomaly. The results show that, in most cases, the anomaly is within ±5% for GHI and ±10% for DNI, using either ground-based irradiance measurements or modeled data from the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗