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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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DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Exploring the potential of non-residential solar to tackle energy injustice

Despite the observed disparities in US residential solar deployment, there is limited insight into whether these disparities exist for the non-residential sector. Here we use DeepSolar, a comprehensive photovoltaic database constructed with satellite imagery, to assess solar deployment equity based on the US Justice40’s disadvantaged community measure. We find that disadvantaged communities have less non-residential solar (–38%), but this disparity is notably higher for residential solar (–67%). Across-state variations are consistent for residential solar (–81% to –49%) yet highly heterogeneous for non-residential solar (–66% to +34%). Using scenarios to explore the potential for microgrids powered by solar on building rooftops larger than 1,000 square metres, we estimate that 63% of disadvantaged communities could meet at least 20% of annual residential electricity demand. Furthermore, our research argues for a new focus on non-residential solar as a way to strengthen resilience and accelerate local deployment of clean energy resources to promote energy justice.

14 SOLAR ENERGY↗
DOE OSTI2023

Impact of system parameters and geospatial variables on the reliability of residential systems with PV and energy storage

A reliable power supply is the foundation of modern society, enabling technologies used to function within a society. Residential systems are places where the end users directly consume power, enabling technologies to sustain life. With the emergence of behind-the-meter resources, the end-users have some control over power supply reliability. The intermittency and variability of these resources impact residential system reliability. In this work, we study the reliability performance of a grid-supplemented residential system with behind-the-meter Distributed Energy Resources(DER) subject to various system parameters and geospatial variables. We propose a multistate reliability model for the behind-the-meter microinverter-based Photo Voltaic (PV) system and integrated inverter-based energy storage (ES) system. A sequential Monte Carlo method is then presented to evaluate the reliability indices for the residential system with behind-the-meter DERs as the main supply and the grid as the backup. The sequential Monte Carlo method is used to analyze the reliability performance of the residential model at the top 100 populous counties of the United States, where actual load and solar irradiance data at the counties is used. In the analysis, the sensitivity of indices to system parameters such as DER size and the sensitivity of the indices to climate zone and gross horizontal irradiation (GHI), which affects the load conditions and the PV output of the residential system, is performed. The analysis results show that the system parameters and the geospatial variables significantly impact the residential system’s reliability. The insights from this analysis will be of immense value to the distribution system planners to provide zone-specific guidelines for DER system sizing and toward the evolution of utility business models. Finally, the methodology developed can be used to extend the analysis to other locations.

14 SOLAR ENERGY↗
DOE OSTI2022

Valuing Residential Energy Efficiency: Analysis for a Prototypical Southeastern Utility [Slides]

The increasing amount of variable renewable energy resources and shifts towards more end-use and vehicle electrification suggests profound changes to power system planning and operation. Specifically, renewable energy is expected to shift net peak demand from late afternoon to early evening and end-use electrification may significantly increase winter peak demand. Residential energy efficiency is likely to align well with these shifts as it tends to produce savings in the early evening (e.g., from lighting measures) and coincident with heating loads (e.g., from envelope and space conditioning measures). Despite the opportunity to decrease system costs and emissions, residential energy efficiency is often limited by static valuation methods and its economic potential is considerably less than its technical potential. Using hourly residential energy efficiency characterizations, utility program cost data, and a capacity expansion model, we estimate the benefits of residential energy efficiency for a prototypical, summer-peaking utility in the Southeastern region. We first establish the cost-effective residential energy efficiency portfolio through “competition” with supply-side resources in a forward-looking capacity expansion model. Importantly, we then evaluate several scenarios intended to drive an increasing amount of cost-effective residential energy efficiency through measure cost reductions, increased customer adoption, policy goals (e.g., carbon price), and delivery of an integrated package of measures. The results quantify total system cost and emissions reductions, fossil-fuel plant retirements, and peak demand reductions. Results suggest the design and prioritization of policies and programs to access the untapped amount of cost-effective residential energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Impacts of COVID-19 related stay-at-home restrictions on residential electricity use and implications for future grid stability

“Stay-at-home” orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. Here, we conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apartment’s consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a possible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is predicted to be 15% – 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% – 53% higher than that under pre-pandemic conditions. We conclude that the projected increase in peak demand - which might arise if stay-at-home guidelines coincided with hot weather conditions - could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Determinants of residential mobility: an adaptive retrospective survey method

This study introduces a survey instrument to collect retrospective life-course events, focusing on residential relocation, and it utilizes the survey to evaluate determinants of residential mobility. Here, the survey consists of seven modules collecting information about household structure and household demographics, latest residential relocation, current and previous home, employment, education, vehicle ownership, and travel behavior. The time window of the life-course calendar in the survey is customized according to the latest residential relocation as an anchor point to assist with memory recollection and balance the required input from participants. The survey is used to collect data from a sample of 514 respondents in Sydney, Australia, and another sample of 404 respondents in Chicago, Illinois, in the US. The Cox proportional hazard model is used to analyze residential mobility. The results show primary school commencement is a salient determinant of residential relocation, but its impact is significantly higher in Chicago compared to Sydney.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Long-term decarbonization impacts on residential energy security across income groups and US states

Abstract The impact of a transition to a net-zero economy on the residential energy sector across diverse income groups in the US remains uncertain. Here, we employ an integrated human-Earth system model, incorporating an expanded set of ten income groups in the residential energy sector, to examine the distributional impacts of long-term decarbonization scenarios on residential energy security at the state level through 2050. We use multiple metrics of energy security, including energy burden, energy satiation gap, and the distribution of energy service across income groups. Our findings show that the net-zero decarbonization scenarios affect residential energy security differently across income groups, with low-to-mid-income groups experiencing larger negative impacts on the dimensions studied here. Comparatively, climate change impact on residential energy security is minor through 2050 based on our model outcomes. Specifically, the net-zero decarbonization scenarios lead to increased energy burden across all income groups and states in 2050, where the lowest (highest) income group in each state shows an average of 0.6 (0.2) percentage point increase in energy burden, relative to the business-as-usual in 2050. The distribution of energy service consumption across income groups is also slightly more skewed under these scenarios. As incomes grow across all deciles in the future, residential energy security generally improves through 2050. Targeted interventions could mitigate the disproportionate impacts that some groups could incur under a transition to a net-zero economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Observations and Lessons Learned From Installing Residential Roofing-Integrated Photovoltaics

Building-sited solar photovoltaics (PV) could play a key role in decarbonizing the building sector either through racked and mounted PV or through Building-integrated PV (BIPV). BIPV is installed into the building envelope itself, with solar cells and/or modules forming the outer layer of a building structure, thus transforming a single-purpose structure into one that serves the dual purposes of the building envelope and electricity. BIPV can be applied to building roofs, facades, awnings, pergolas, windows, skylights, balustrades, and other external surfaces. Given BIPV products vary widely, the focus of this research is residential roofing integrated PV (RIPV), where solar is incorporated into or otherwise replaces the roofing material. Previous research suggests that residential RIPV could reduce customer acquisition, labor, supply chain, and equipment costs. These products have yet to realize these cost savings and deployment remains significantly less than conventional rooftop PV as a relative share of the addressable market in the US. One potential barrier to broader residential roofing integrated PV deployment may be higher costs relative to conventional rooftop PV, primarily because the design and installation of these products is still evolving. Here, we explore residential RIPV cost-reduction opportunities by analyzing installation processes. Our study documents residential RIPV installations at 2 reroofing sites and the equivalent of 9 new construction sites in California through a methodology known as time and motion study. We also conducted interviews with subject-matter experts to identify barriers and solutions to maximize these products' market penetration. Our time and motion study breaks the RIPV installation process into four steps: 1) staging, unloading, and roof preparation; 2) fire resistant underlayment(s) (synthetic material laid between roof shingles and roof deck); 3) flashings and PV installation; and 4) wiring and monitoring. We measure the time required for each step in terms of worker-hours, representing an hour of labor from a single worker. We further normalize process time by dividing worker-hours by kilowatt (kW) of system capacity. The most time-intensive step was flashings and PV installation, taking around 2.4 worker-hours per kW on average and accounting for around 60% of the process time for an average installation. The total installation process took on average about 6.4 and 3.5 worker-hours per kW at the reroofing sites and new construction sites, respectively. For comparison, a previous time and motion study documented a time of 6.9 worker-hours per kW for conventional rooftop PV. The shorter RIPV installation times are consistent with previous studies suggesting that RIPV could be installed faster than conventional rooftop PV. The time and motion results and feedback from interviewees provide insights into potential residential RIPV cost reduction opportunities. Several interviewees suggested that these products would be more efficient if PV installation was more fully integrated into the roofing/construction industries, which currently use separate supply chains and skillsets. Further integration could reduce supply chain delays and labor force redundancies. Future research could explore specific ways to integrate these industries to help realize the cost savings potential of RIPV.

14 SOLAR ENERGY↗
DOE OSTI2026

A Physical Model Enhanced Data Driven Method for High-Resolution Residential Load Profile Generation

Residential buildings account for significant energy consumption, creating opportunities to offer grid services. As electric utilities seek to implement effective system operation strategies, understanding residential energy consumption patterns becomes essential; However, the time intervals of load profiles measured by utilities' smart meters are typically from 15 minutes to 60 minutes. The low-resolution data make it hard to extract appliance-level load information, which is critical for providing grid services. This paper presents a load profile generator designed to produce synthetic load profiles for residential buildings that emphasizes the importance of accurate representations of realistic energy consumption patterns. The generator takes realistic low-resolution residential load measurements and weather data as inputs, producing 1-minute interval profiles that match the characteristics of the original profiles. Further, this generator can be used to populate load profiles in areas where actual measurements are limited to improve the ability of utilities to analyze their distribution systems. By providing more high-resolution residential building load profiles, this tool supports electric utilities to enhance their residential building load control strategies and improve overall grid stability.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Synthetic residential load models for smart city energy management simulations

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterize the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Online Calculator to Evaluate the Impact of Airtightness on Residential Building Energy Consumption and Moisture Transfer

Energy consumption in residential buildings is primarily driven by space conditioning applications. Space heating and cooling, on average, consume approximately 50% of the energy in the residential buildings in the U.S. The primary energy use due to infiltration is more than 2.8 Quads, which is 29% of primary energy consumption attributable to fenestration and building envelope components in residential buildings in US in 2010. There are advanced air barrier technologies and construction practices to reduce air leakage in buildings, which are currently available in the market. However, the lack of adequate information on their impact on energy consumption and the durability of buildings has caused the slow adoption of these technologies and methods. In the past, the authors developed an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in airtightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations, given that air leakage through the building envelope can have a significant impact on moisture transfer. The calculator is again being expanded by adding residential and additional commercial building data. In this paper, we present the impact of airtightness in residential buildings on energy consumption and moisture transfer. The study includes the analysis of airtightness in 52 major cities in the U.S. and five cities in Canada on a residential building that includes a crawlspace and has a gas furnace.

Kunwar, Niraj↗
DOE OSTI2025

Residential and Small Commercial Solar Photovoltaic and Storage Permitting, Inspection, and Interconnection Timelines: A Retrospective Review (2017-2023)

This report is part of the ongoing Solar Time-Based Residential Analytics and Cycle Time Estimator (SolarTRACE) project, led by the National Renewable Energy Laboratory (NREL). The SolarTRACE project utilizes time-stamped project-level data provided by installer-partners to assess nationwide and AHJ- and utility-level PI&I and other solar PV adoption timelines since 2017. Our dataset now covers 22% of residential solar and 33% of residential storage installs in the U.S. since 2017. This report provides an update to our previous 2022 report (Cruce et al., 2022b) and includes: updated 2017 2023 project timelines for residential rooftop solar PV up to 20kW; updated tracking of permitting process changes at nearly 4,000 AHJs nationwide; and first-ever reporting of timelines for residential PV+storage projects up to 20kW.

14 SOLAR ENERGY↗
DOE OSTI2023

Towards COP27: Decarbonization patterns of residential building in China and India

As the two largest emerging emitters with the highest growth in operational carbon emissions from residential buildings, the historical emission patterns and decarbonization efforts of China and India warrant further exploration. This study aims to be the first to present a carbon intensity model considering end-use performances, assessing the operational decarbonization progress of residential building in India and China over the past two decades using the newest decomposing structural decomposition approach. Results indicate (1) the annual operational carbon intensity increased by 1.4% and 2.5% in China and India, respectively, between 2000 and 2020. Household expenditure-related energy intensity and emission factors were crucial in decarbonizing residential buildings. (2) Building electrification played a significant role in decarbonizing space cooling (–87.7 in China and – 130.2 kg of carbon dioxide (kgCO 2 ) per household in India) and appliances (~ –169.7 in China and ~ –43.4 kgCO 2 per household in India). (3) China and India collectively decarbonized 1498.3 and 399.7 M-tons of CO 2 in residential building operations, respectively. In terms of decarbonization intensity, India (164.8 kgCO 2 per household) nearly caught up with China (182.5 kgCO 2 per household) in 2020 and is expected to surpass China in the upcoming years, given the country's robust annual growth rate of 7.3%. Overall, this study provides an effective data-driven tool for investigating the building decarbonization potential in China and India, and offers valuable insights for other emerging economies seeking to decarbonize residential buildings in the forthcoming COP28 1 age.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A conceptual framework for residential energy security in the context of clean energy transitions

Energy security is a crucial aspect of human well-being. As climate change impacts become more evident, countries are constructing equitable, resilient, and sustainable clean energy transition policies to reduce emissions while ensuring energy security. Climate policies globally highlight the importance of national energy security. Furthermore, adequate and affordable access to household energy is also critical to the continued prioritization of climate mitigation. However, past energy security discussions within the broader climate research and policymaking community primarily focused on national-level energy supply as a critical metric of energy security. Less research has explored the potential implications of energy transitions for residential energy security, often focusing on a single dimension of residential energy security. Thus, we conduct a review of journal articles and governmental plans to develop a conceptual framework of residential energy security and facilitate communication among researchers and policymakers. The framework is designed around four foundational pillars, five metrics measuring residential energy security, and seven drivers influencing the metrics. Additionally, we provide policy examples to show how this framework can be applied to inform decision-making. Thus, this paper makes important contributions to the literature by (a) creating a framework to better understand the concept of energy security at the household level for future research and policy-relevant communications, (b) identifying gaps in the current literature, and (c) highlighting instances where aspects of residential energy security are discussed in policies and governmental plans, which help serve as guiding examples for future applications of our framework in the policymaking processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Assessing outdoor air quality and public health impact attributable to residential black carbon emissions in rural China

Black carbon (BC) is a significant component of particulate matter (PM) that relates to air pollution, climate forcing, and further implications for public health. BC is predominantly released from the combustion of solid fuels. Combustion of low-quality fuels in rural China may induce severe respiratory and cardiopulmonary health outcomes for residents, which have however been inadequately assessed. One major reason for the limited understanding is the lack of a high-resolution inventory. An improved method of estimating the BC-associated public health burden is needed. This work quantified premature mortalities due to residential BC emissions in rural China. Domestic BC emissions at 1×1 km resolution were compiled based on previous field investigation, which were further configured for air quality simulation. A chemistry transport model, WRF–CMAQ v5.2, was employed for simulating BC concentrations. The consequent premature mortalities were quantified by a BC-specific concentration-response function (CRF) derived from an epidemiological study. Results show that residential combustion of solid fuel in rural China emitted 648.0 Gg (95%CI: 361.0–965.9) BC in 2014, after dispersion, accounting for 51.8% of annual mean ground-level BC concentration in China. Such impact was most severe in North and Northeast China, and the Sichuan Basin. The further investigation estimated 171,000 (95%CI: 69,000–387,000) premature mortalities that were attributable to exposure to rural residential BC. These findings reveal the major contribution of rural residential BC emissions to air pollution formation and public health impacts. Our findings are anticipated to provide useful information for enacting the next-stage environmental strategy for the residential sector in China.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure

In March 2021, the cumulative sale of plug-in electric vehicles (PEVs), including plug-in hybrid electric vehicles (PHEV) and battery electric vehicles (BEV), reached 1.8 million in the United States (Argonne National Laboratory 2021). However, PEV adoption is still in its infancy; its market share has just reached around 3% of new light-duty vehicle (LDV) sales by the end of 2020 (Alliance for Automotive Innovation 2021). Current trends suggest that PEV market share in the United States is increasing. The U.S. Energy Information Administration's (EIA's) 2020 Annual Energy Outlook forecasts PEV registrations to exceed 8 million vehicles by 2030 (AEO 2020). PEV adoption is expected to be led by states that are regulating the sale of zero emission vehicles (ZEVs) (California Air Resources Board). California continues to push for more aggressive ZEV regulations; the state recently issued an executive order aimed at 100% of LDV sales being ZEVs by 2035 (Office of Governor Newsom). At the federal level, the Biden administration has shown great ambition in encouraging broader electric vehicle (EV) adoption, including setting the goal of installing 500,000 new chargers nationwide (The White House 2021). Access to charging infrastructure is consistently cited as one of the primary barriers to the increased sale of PHEVs and BEVs (Carley et al. 2019). In the United States, PEV charging options are often described using a pyramid structure, with residential charging as the foundation, workplace charging in the middle, and public charging on top (Figure 1). The existing electricity system, which generates, transmits, and distributes electric fuel to residential households, has helped PEVs partially overcome the "chicken and egg" conundrum that has haunted other alternative fuels. Viable home access to electric charging is also an important equity issue, because non-residential PEV charging options (e.g., workplace or public charging stations) are generally more expensive. Households without residential charging access may experience higher total cost of PEV ownership if non-residential charging options are more costly.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Implications of different income distributions for future residential energy demand in the U.S.

Abstract Future income distribution will affect energy demand and its interactions with various societal priorities. Most future model simulations assume a single average consumer and thus miss this important demand determinant. We quantify long-term implications of alternative future income distributions for state-level residential energy demand, investment, greenhouse gas, and pollutant emission patterns in the United States (U.S.) by incorporating income quintiles into the residential energy sector of the Global Change Analysis Model with 50-state disaggregation. We find that if the income distribution within each U.S. state becomes more egalitarian than present, what means that the difference on income between the richest and poorest decreases over time, residential energy demand could be 10% (4%–14% across states) higher in 2100. This increase of residential energy demand will directly reduce energy poverty, with a very modest increment on economywide CO 2 emissions (1%–2%). On the other hand, if U.S. states transition to a less equitable income distribution than present, with the difference between richest and poorest increasing over time, residential energy demand could be 19% (12%–26% across states) lower. While this study focuses on a single sector, we conclude that to improve understanding of synergies and tradeoffs across multiple societal goals such as energy access, emissions, and investments, future model simulations should explicitly consider subregional income distribution impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort

The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗