Persistent impacts of covid pandemic on residential electricity consumption

Persistent impacts of covid pandemic on residential electricity consumption | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Persistent impacts of covid pandemic on residential electricity consumption Jim McMahon, Joe Long This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6474769/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In response to the covid pandemic, residential electricity use changed in 2020. In California, government-mandated lockdowns closed businesses and resulted in many people spending more time at home. In 2021 and 2022, most people returned to work, as evidenced by location tracking of cell phones. This paper describes analysis of monthly residential electricity consumption at the county level for California from 2017 to 2022. Results show that residential electricity consumption increased in 2020 and did not return to 2019 levels in either 2021 or 2022. Since hot weather is the primary driver of change in monthly residential electricity use in California, the dependence of residential electricity use on cooling degree days was analyzed. Warmer weather does not explain the increase. Results show that both non-cooling (“baseline”) electricity use increased, perhaps due to new equipment in homes, and that hot weather electricity use also increased compared to historical years. Both effects were observed for the service territories of most utilities in California to varying degrees. Future research will examine possible explanations, including conversion of existing or new floorspace in homes into office space, additional equipment (air cleaners, office equipment), and behavioral changes (hours of use, temperature set-points). residential electricity covid cooling Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION A shift toward higher residential energy consumption has been reported during the COVID-19 pandemic starting in 2020, when many people were forced to work from home. For the United States, residential consumption increased 7.9% in 2020 compared to 2019. (Cicala, 2023 ) In 2020, homes in Austin, Texas, showed increased non-HVAC energy use and higher HVAC loads compared to the same temperatures in previous years (Kawka and Cetin, 2021 ). Krarti and Aldubyan ( 2021 ) identified increases in residential electricity for Melbourne, Australia of 14% (Farrow, 2020 ), 17% in the United Kingdom (Gausden, 2020 ), and 11–20% in Ireland (Savills News, 2020 ). In Warsaw, residential electricity increased 6.74% from March/April 2018 to 2020 (Bielecki, et al., 2021 ). In Manzanilla, Spain, residential electricity increased 15% during lockdown and 7.5% in the reopening period (Garcia et al, 2021 ) Some households in India increased average daily electricity 26% during lockdown with 45–60% increases in air conditioning, while others reduced AC and electricity to mitigate power outages and electricity expenses (Debnath, 2022). In China, the annual rate of increase in residential electricity power consumption increased from pre-pandemic (2016–2019) 8.64% and 8.07%, urban and rural, to 9.71% and 12.24% from 2020–2022, respectively, with significant differences among provinces, perhaps reflecting population mobility and economic differences (Du, et al, 2024 ). Changes could be due to more hours at home, increases in spaces provided with space conditioning, or new equipment, such as air cleaners or office equipment. Forecasts of future electricity consumption (California Energy Commission, 2024 ), depend in part on whether changes due to the pandemic were transient, such that they will revert over time, or whether some of those changes persist. This paper examines monthly residential electricity consumption in California from 2017 to 2022 to address the following research questions: 1) how did residential electricity consumption change during and after covid? 2) is residential electricity consumption on track to return to pre-covid levels; 3) to what extent are changes in residential electricity consumption explained by hot weather; and 4) does mobility data, specifically weekday hours at home as measured by cell phone location data, correlate well with residential electricity consumption. If mobility data correlated well with residential electricity consumption, it might be used as an indicator of future consumption. DATA Monthly residential electricity consumption and cooling degree days (CDD) by county were obtained from the California Energy Commission. (Harms, 2023 ) CDD are base 65 degrees Fahrenheit. Annual population data by county was examined from two sources, United States Census Bureau (2023) and California Department of Finance ( 2023 ). Google ( 2023 ) collected mobility data for weekdays from January 2020 through October 2022. Using the location of cell phones, estimates were made by county by day for the number of weekday hours at home. All values are expressed as percent change from the January 2019 baseline for the same day of the week, weekdays only. METHOD This paper presents an original analysis of changes in California annual and monthly residential electricity consumption from 2017 through 2022. The trend is analyzed to provide a basis for forecasting future residential electricity consumption. Annual residential electricity consumption in California was calculated as the sum over counties and months for each year, 2017–2022. The years 2017–2019 were treated as pre-covid and 2020–2022 as covid years. Residential electricity consumption for California by county and by utility service territory (sum over counties) was analyzed. Hot weather drives monthly variation in residential electricity consumption. Consumption typically increases with hotter temperatures (more cooling degree days). A regression was derived from monthly consumption and cooling degree days for each year, and for the two three-year periods (2017–2019 and 2020–2022). Three elements of change were identified and quantified: a) the intercept of the regression was interpreted as baseline (non-cooling) electricity; b) the slope (kWh/CDD) was analyzed as cooling; c) the change in slope after 2019 was interpreted as the change in electricity consumption related to hot weather. The change in slope is interpreted as primarily air conditioning but could be any electricity consumption associated with warmer temperatures. RESULTS The analysis provided the following results: 1) Annual residential energy consumption in California increased after 2019 and remained higher through 2022; California residential electricity consumption increased from 92,724 gigawatt hours (GWh) in 2019 to 102,945 GWh in 2020, an increase of 10,222 GWh (11.0%). The highest previous year was 2017 at 93,375 kWh. Population in California declined while residential electricity consumption increased. 2) Electricity consumption increased for non-cooling and cooling-related uses. 3) The amount of electricity consumed in comparably hot months has increased significantly. 4) Most of the increase in consumption is not associated with hot weather. ANNUAL RESIDENTIAL ELECTRICITY CONSUMPTION IN CALIFORNIA INCREASED AFTER 2019 Table 1 shows that California residential electricity consumption increased in 2020 by 11.0% compared to 2019, remained 8.4% higher than 2019 in 2021, and increased to 11.7% higher than 2019 in 2022. While one year may be unusual, a comparison was made of two three-year periods, 2017-2019 in comparison to 2020-2022 (bottom of table 1). The change from 2017-2019 to 2020-2022 was an increase of 29,211 GWh (average 9,737 GWh per year) or 10.5%. The trend resembles a step up in 2020 and continuing at a new higher level through 2022. Table 1. California Annual Residential GWh and CDD compared to 2019 Annual Residential GWh Change in GWh from 2019 as % California population weighted CDD Change in CDD from 2019 as % 2017 Total 93,375 0.7% 1,483 19.4% 2018 Total 91,760 -1.0% 1,312 5.6% 2019 Total 92,724 0.0% 1,243 0.0% 2020 Total 102,945 11.0% 1,573 26.6% 2021 Total 100,536 8.4% 1,268 2.1% 2022 Total 103,589 11.7% 1,418 14.1% Residential GWh Change from 2017-2019 GWh as % California population weighted CDD Change in CDD from 2017-2019 as % 2017-2019 277,859 0.0% 4,038 0.0% 2020-2022 307,070 10.5% 4,259 5.5% WARMER WEATHER DID NOT SIMPLY EXPLAIN HIGHER ANNUAL RESIDENTIAL ELECTRICITY CONSUMPTION Hot weather leads to higher electricity consumption, particularly by air conditioners and fans to cool homes. Hot weather is the primary driver of differences in California residential electricity consumption from month to month. Cooling degree days (CDD) by county were weighted by county population to obtain California population weighted CDDs for each year. Population-weighted CDDs in 2020 (1,573) were higher than 2019 (1,243) by 26.6% and annual residential electricity consumption was higher by 11.0%. CDD were higher in 2020 than 2019, which accounts for some of the increase. Comparisons of 2021 and 2022 to previous years in Table 1 show that changes in annual CDD do not simply explain changes in residential GWh. CDDs in 2021 (1,268) were similar to (2% higher than) CDDs in 2019 (1,243) and residential electricity consumption in 2021 (100,536 GWh) was 8.4% higher than in 2019 (92,724), an increase of 7,812 GWh. Population-weighted cooling degree days in 2022 (1,418) were 4.4% lower than 2017 (1,483), but residential electricity consumption in 2022 (103,589 GWh) was higher than 2017 (93,375) by 10,214 GWh (10.9% higher) ELECTRICITY CONSUMPTION INCREASED FOR NON-COOLING USES AND FOR COOLING The need for cooling is a significant explanatory variable for residential electricity consumption, explaining much of the month-to-month variation, with California monthly consumption ranging from about 6,000 to 12,000 GWh per month, highest in the summer months. The relative contributions of three factors were considered in explaining the difference between annual residential electricity consumption in covid (2020-2022) compared to baseline (2017-2019) periods: cooling degree days, change in slope of monthly GWh to CDD, and intercept. Figure 1 illustrates a regression of monthly GWh against monthly CDD providing an intercept and a slope for each period. The intercept was interpreted as non-CDD-dependent GWh. Annual non-CDD-dependent GWh were calculated as 12 times the intercept. Annual CDD-dependent GWh were calculated as annual GWh minus non-CDD-dependent GWh. Figure 2 shows California monthly residential electricity consumption and state-wide population-weighted cooling degree days for 2017 to 2022. To test whether a significant change has occurred, the data were combined for each three-year period. Two linear regressions are shown, one for 2017 to 2019 (pre-covid) and one for 2020-2022 (covid). The relationship between CDD and residential electricity consumption changed after 2019 to a steeper slope of electricity consumption per CDD. Baseline (non-cooling) residential electricity consumption also increased (intercept). This indicates that both non-cooling electricity (intercept) and cooling in response to temperatures (slope) remain higher than the historical trend observed through 2019. Based on a t-test, we can say with 95% certainty that California residential electricity consumption in 2017-2019 is lower than in 2020-2022. [1] The dependence of monthly residential electricity consumption on CDD was derived for each year, 2017 to 2022. Figure 3 shows the data and linear regressions fit for each year. As noted previously, the range of cooling degree days is similar for most of the years, but the residential electricity consumption is higher in 2020, 2021, and 2022 than in previous years. The linear regressions show that from 2017 to 2019, the slope GWh/CDD is 8.38 to 10.39, while for 2020-2022, the slope is 11.32 to 12.30. Monthly electricity consumption at the same CDD is higher after 2019. In addition, the intercepts have changed. From 2017-2019, the intercepts ranged from 6,532 to 6,858 GWh, and from 2020-2022 the intercepts ranged from 7,094 to 7,178 GWh. In 2019, California residential electricity consumption was 92,724 GWh. Based on a linear regression of monthly residential electricity consumption to monthly CDD, the intercept is 6,858.5 GWh per month (times 12 = 82,302 GWh per year). The contribution dependent on CDD is 10,422 GWh per year (total annual GWh minus 12* intercept). Table 2. CDD-dependent and non-CDD-dependent residential GWh for California, 2017-2022 Annual Residential GWh Non-CDD dependent (12*intercept) GWh CDD-dependent GWh 2017 Total 93,375 78,709 14,666 2018 Total 91,760 78,390 13,370 2019 Total 92,724 82,302 10,422 2020 Total 102,945 85,134 17,811 2021 Total 100,536 85,504 15,032 2022 Total 103,589 86,143 17,446 Average annual Residential GWh Average annual Non-CDD dependent GWh Average Annual CDD-dependent GWh 2017-2019 92,620 79,800 12,819 2020-2022 102,357 85,594 16,763 Table 2 shows for years 2017-2022 the total GWh, non-CDD-dependent GWH (12*intercept), and the CDD-dependent GWh. When comparing covid impact to baseline, the percent of total change was attributed to intercept (non-CDD-dependent GWh), cooling degree days (at baseline slope), and change in slope of GWh to CDD. Table 3 shows that the change in intercept accounts for 60% of the total change (5,793 of 9,737 average annual GWh), change in slope accounts for 34% (3,944 GWh), and change in CDD accounts for 6% (619 GWh). Table 3. California changes in residential electricity consumption in 2020-2022 compared to 2017-2019 (pre-covid) Residential GWh Change in GWH in 2020-2022 compared to 2017-2019 (pre-covid) Percent of Total Change in 2020-2022 GWh compared to 2017-2019 (pre-covid) Average annual Residential GWh Average annual Non-CDD dependent GWh Average Annual CDD-dependent GWh Average annual total change in GWh Average annual change in non-CDD-GWh Average annual change in GWh from change in CDD Average annual change in GWh from change in slope Percent of total change from Non-CDD-dependent GWh Percent of total change from change in CDD Percent of total change from change in slope of GWh to CDD 2017-2019 92,620 79,800 12,819 - - - - 2020-2022 102,357 85,594 16,763 9,737 5,793 619 3,325 60% 6% 34% COOLING AND NON-COOLING ELECTRICITY BY UTILITY SERVICE AREA Monthly county-level data for 2017 to 2022, including residential electricity consumption and population-weighted cooling degree days, was mapped onto major utility service areas. The correlation between monthly residential electricity consumption and monthly (population-weighted) cooling degree days was analyzed for each year, 2017-2021 individually, and for two three-year-combined sets, 2017-2019 (pre-covid) and 2020-2022 (covid impact). For all major utilities except SMUD, the covid impact increased both the intercept (non-CDD-dependent GWh) and the slope of GWh vs CDD. For SMUD, the intercept increased, but the slope is not changed. For LADWP, although the slope increased, the number of CDD was 10% lower in 2020-2022 than in 2017-2019. Results differed among the utility service territories.[2] Comparing 2020-2022 (covid impact) to 2017-2019 (baseline), Table 4 shows that the covid impact was an annual average increase for each utility ranging from +5.3 to +12.8%. The intercept (non-CDD-dependent GWh) contributed 42 to 65% of this change, the change in slope of GWh to CDD contributed -0.5 to 48.9% of the total change and change in CDD contributed -13 to +58%. Table 4. Changes in residential electricity in 2020-2022 compared to 2017-2019 (pre-covid) 2020-2022 Residential GWh Change in GWh in 2020-2022 compared to 2017-2019 (pre-covid) Percent of total change in 2020-2022 GWh compared to 2017-2019 (pre-covid) Average annual Residential GWh Average annual Non-CDD dependent GWh Average Annual CDD-dependent GWh Average annual total change in GWh Average annual change in non-CDD-GWh Average annual change in GWh from change in CDD Average annual change in GWh from change in slope Percent of total change from Non-CDD-dependent GWh Percent of total change from change in CDD Percent of total change from change in slope of GWh to CDD PG&E 34,449 30,751 3,698 2,846 (+9%) 1,778 329 739 62.5% 11.6% 26.0% SCE 40,046 31,002 9,044 4,547 (+12.8%) 2.399 188 1,960 52.8% 4.1% 43.1% SDGE 7,898 7,002 896 695 (+9.7%) 455 30 211 65.4% 4.2% 30.3% SMUD 5,059 4,234 825 254 (+5.3%) 107 149 -1 42.0% 58.5% -0.5% LADWP 8,218 6,930 1,288 766 (+11.9%) 494 -102 375 64.4% -13.4% 48.9% WEEKDAY HOURS AT HOME The section presents data on the changes in number of hours at home for residents of California counties from March 2020 to October 2022, compared to 2019. Lockdowns in response to covid-19 in April 2020 increased the number of hours at home by about 20% (simple average across counties). Hours-at-home decreased over time during 2020-2022, with upticks during periods of higher levels of covid-19 (e.g., January 2021, January 2022, and July 2022). After the initial lockdown, hours-at-home generally declined until 2022, with some upticks in response to higher covid levels, particularly in January 2021, January 2022, and July 2022. Attempts to correlate hours at home with monthly residential energy consumption for selected counties failed to show a high correlation. Figures 5 and 6 show examples for Los Angeles and Alameda Counties, respectively. The large variations in residential electricity consumption from month to month are correlated with weather (e.g., cooling degree days), not with hours-at-home. Figure 7 shows changes expressed as percent change from 2019 for California state-wide annual residential electricity consumption (GWh), weekday hours-at-home, and population. California residential electricity increased after 2019 and has remained higher in 2021 and 2022, while population has declined. Hours at home increased in 2020 and has declined in 2021 and 2022. Mobility data documents hours-at-home by county by month for 2020-2022. Residential electricity consumption increased in 2020, mostly in line with hours-at-home. Hours-at-home peaked in early 2020, generally declined until 2022, with upticks during surges of covid cases. In 2022, while hours-at-home continued to move back toward 2019 values, residential electricity consumption remained high. [1] The t stat is -2.246 for a one-tailed test with 35 observations. [2] PG&E is Pacific Gas and Electric. SCE is Southern California Edison. SDGE is San Diego Gas and Electric. SMUD is Sacramento Municipal Utility District. LADWP is Los Angeles Department of Water and Power. CONCLUSIONS AND DISCUSSION Residential electricity consumption increased in 2020 and remained higher than historical levels in 2021 and 2022. Both non-CDD-related and CDD-related electricity increased and remains higher. More research is needed to allocate these changes to end uses, that is, to determine whether changes are due to conditioned space (such as conversions to office space), specific types of equipment (such as air cleaners or home office equipment) or to usage behavior (such as more cooling hours or lower temperature setpoints). The implication is that future California residential electricity consumption is likely to remain higher than historical trends until 2019 would have suggested. As data on residential electricity consumption continues to be accumulated in future, analysis should continue to evaluate the degree to which higher residential electricity consumption persists or whether it is returning to previous levels. Increases in hours-at-home on weekdays, based on mobility data, are not well correlated with the changes in residential monthly electricity consumption at the county level for the period 2020 to 2022. The mobility data did not include weekends. The analysis to date was not able to establish the use of mobility data (weekday hours-at-home) as a good predictor of residential electricity consumption. The changes in residential electricity consumption initiated during covid are persisting, even as workers return to work or to hybrid schedules (working some days at home). LIMITATIONS AND FUTURE WORK This study was limited to California and its counties. This study was limited to total residential electricity. Future work can be directed to more disaggregated analysis. Additional research on load profiles and end uses (equipment saturations and usage behaviors) since 2019 is recommended to allocate the changes to end uses and times of day. Continued tracking of load profiles and end use consumption is recommended to evaluate any potential trend since 2020 that might provide insight into future residential electricity consumption in California. This research could include a) Longitudinal studies of a sample of households having hourly or finer consumption data from 2019 to 2022 to determine changes in electricity usage profiles; b) Surveys and behavioral studies to inform estimates of changes in usage and hourly profiles by end use; c) Future work could examine residential natural gas consumption. The mobility data cited here regarding weekday hours-at-home was only available from March 2020 through October 2022. A source of mobility data that continues over time could be used as an indicator of return to some behavior to 2019 levels, although direct studies of actual behaviors may provide more insight. Declarations FUNDING DECLARATION: This work was conducted under subcontract to Aspen Environmental Group (Subcontract No. 1980-000-03) for California Energy Commission (CEC) Work Authorization # 1981.003 in support of subtask 4, Calibration, specifically, calibration for covid impacts after 2019. CONFLICT OF INTEREST STATEMENT: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution J.M. designed and conducted the analysis and wrote the paper. J.L. contributed data, prepared one figure, and reviewed the paper. Acknowledgement This work was conducted under subcontract to Aspen Environmental Group (Subcontract No. 1980-000-03) for California Energy Commission (CEC) Work Authorization # 1981.003 in support of subtask 4, Calibration, specifically, calibration for covid impacts after 2019. We want to thank Taylor Harms and other CEC staff for support, data, discussion, and review of this work. Data Availability The author confirms that all data generated or analysed during this study are included in this published article. References Bielecki, S.; Skoczkowski, T.; Sobczak, L.; Buchoski, J.; Macia˛g, Ł.; Dukat, P. (2021), Impact of the Lockdown during the COVID-19 Pandemic on Electricity Use by Residential Users. Energies , 14, 980. https://doi.org/10.3390/en14040980 California Department of Finance, (2023), CA Total Population. July 1 Estimates and Projections, https://dof.ca.gov/forecasting/demographics/estimates/ Last Updated 7/19/2023. 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Personal communication, Taylor Harms, California Energy Commission, August 8, 2023. QFER data in Dropbox. Monthly residential GWh by county 1985-2022. Consumption data is publicly available at Electricity Consumption by County Kawka, E. and Cetin, K.(2021), Impacts of COVID-19 on residential building energy use and performance, Building and Environment 205, 108200. https://doi.org/10.1016/j.buildenv.2021.108200 Krarti, M. and Aldubyan, M. (2021), Review analysis of COVID-19 impact on electricity demand for residential buildings . Renewable and Sustainable Energy Reviews 143, 110888. https://doi.org/10.1016/j.rser.2021.110888 Savills News (2020), COVID-19 restrictions changing the daily patterns of energy consumption. https://www.savills.us/insight-and-opinion/savills-news/299070/covid-19- restrictions-changing-the-daily-patterns-of-energy-consumption United States Census Bureau, County Population Totals and Components of Change: 2020-2022. https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-total.html Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6474769","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":448421605,"identity":"a61b3e5e-eb31-4fab-8f2b-ed9f0ba7bd23","order_by":0,"name":"Jim McMahon","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACxmYGxscw9oEECN3AUIFfC7MxA4OBBIgD0iIB1nIGv0Vs0nAtDGAtQIBPC3M7d1p1QcWfOn7pww8OPMyxq+NnYG57cACPyxibebfdnnHGQEKyL83gQOK2ZAnJBsZ2gwN4rAFr4W0zkDA4w8MA1MIsYXCAsU36Yxt+LcW8/wwk7CFa6iXsgVokDhLQwszbALSFB6zlsIQBA2Etm6VnHDOWnHGGDeSX45IzDgO14POLYf/ZjZ8LauT4+XuYHz78ua2an7+9/ZkEvhAzbMAQYsatGgzkCciPglEwCkbBKGBgAACuvE/+u6mteQAAAABJRU5ErkJggg==","orcid":"","institution":"Better Climate Research and Policy Analysis","correspondingAuthor":true,"prefix":"","firstName":"Jim","middleName":"","lastName":"McMahon","suffix":""},{"id":448421606,"identity":"e8a35e48-4311-44e8-b47b-63c77b39fc44","order_by":1,"name":"Joe Long","email":"","orcid":"","institution":"Aspen Environmental Group","correspondingAuthor":false,"prefix":"","firstName":"Joe","middleName":"","lastName":"Long","suffix":""}],"badges":[],"createdAt":"2025-04-17 23:08:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6474769/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6474769/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81510307,"identity":"d1df3930-a73d-4d6e-b6ed-e142c4b973c1","added_by":"auto","created_at":"2025-04-28 06:04:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":37039,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIllustrative Example of Monthly Total GWh and Non-CDD-dependent GWh\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/f50512a2dd2d50dc18767274.png"},{"id":81510497,"identity":"9d925818-10ab-4da4-aac0-45cc86992eeb","added_by":"auto","created_at":"2025-04-28 06:04:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":85346,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/73307e91531c9e89143413e0.png"},{"id":81510347,"identity":"59e16819-8f05-4c25-b28e-e695ab8a28ca","added_by":"auto","created_at":"2025-04-28 06:04:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":117698,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/77e34d0cdd1f31d92fcdcdb4.png"},{"id":81510516,"identity":"01652830-8834-42d8-aa07-308e495217f9","added_by":"auto","created_at":"2025-04-28 06:04:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":168323,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/a87cc9a3cdfd4d71abbaae9d.png"},{"id":81510200,"identity":"252c6e20-452f-4776-add7-1b0b3a6a9842","added_by":"auto","created_at":"2025-04-28 06:04:40","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":86909,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLos Angeles County 2020-2022.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(left) A. Percent change in monthly residential GWH by month. (right) B. Percent change in residential monthly GWh vs % change from 2019 in weekday hours-at-home.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/74ba3587c5df42fbfdf1c8f6.png"},{"id":81510365,"identity":"4f329f9f-ea2e-4821-bdc4-8f6854f33fb4","added_by":"auto","created_at":"2025-04-28 06:04:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":80442,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlameda County 2020-2022. (left) A. Percent change in monthly residential GWH by month. (right) B. Percent change in residential monthly GWh vs % change from 2019 in weekday hours-at-home.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/eb6b1af615233ddedc0a2621.png"},{"id":81510426,"identity":"214436fe-2ab3-4b6d-8808-51e91d8dd1a8","added_by":"auto","created_at":"2025-04-28 06:04:54","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":79334,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePercent change from 2019 for California annual residential electricity consumption, weekday hours-at-home, and population.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/91cb38e8f9ab906d10cc196e.png"},{"id":98624255,"identity":"5dffb69b-6b81-4ee7-80f9-ee5b6d330fc8","added_by":"auto","created_at":"2025-12-19 17:08:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1698151,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6474769/v1/923281eb-d578-40e2-867c-398da0914c28.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Persistent impacts of covid pandemic on residential electricity consumption","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eA shift toward higher residential energy consumption has been reported during the COVID-19 pandemic starting in 2020, when many people were forced to work from home. For the United States, residential consumption increased 7.9% in 2020 compared to 2019. (Cicala, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) In 2020, homes in Austin, Texas, showed increased non-HVAC energy use and higher HVAC loads compared to the same temperatures in previous years (Kawka and Cetin, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Krarti and Aldubyan (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) identified increases in residential electricity for Melbourne, Australia of 14% (Farrow, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), 17% in the United Kingdom (Gausden, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and 11–20% in Ireland (Savills News, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In Warsaw, residential electricity increased 6.74% from March/April 2018 to 2020 (Bielecki, et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In Manzanilla, Spain, residential electricity increased 15% during lockdown and 7.5% in the reopening period (Garcia et al, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) Some households in India increased average daily electricity 26% during lockdown with 45–60% increases in air conditioning, while others reduced AC and electricity to mitigate power outages and electricity expenses (Debnath, 2022). In China, the annual rate of increase in residential electricity power consumption increased from pre-pandemic (2016–2019) 8.64% and 8.07%, urban and rural, to 9.71% and 12.24% from 2020–2022, respectively, with significant differences among provinces, perhaps reflecting population mobility and economic differences (Du, et al, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChanges could be due to more hours at home, increases in spaces provided with space conditioning, or new equipment, such as air cleaners or office equipment. Forecasts of future electricity consumption (California Energy Commission, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), depend in part on whether changes due to the pandemic were transient, such that they will revert over time, or whether some of those changes persist. This paper examines monthly residential electricity consumption in California from 2017 to 2022 to address the following research questions: 1) how did residential electricity consumption change during and after covid? 2) is residential electricity consumption on track to return to pre-covid levels; 3) to what extent are changes in residential electricity consumption explained by hot weather; and 4) does mobility data, specifically weekday hours at home as measured by cell phone location data, correlate well with residential electricity consumption. If mobility data correlated well with residential electricity consumption, it might be used as an indicator of future consumption.\u003c/p\u003e\n\u003ch3\u003eDATA\u003c/h3\u003e\n\u003cp\u003eMonthly residential electricity consumption and cooling degree days (CDD) by county were obtained from the California Energy Commission. (Harms, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) CDD are base 65 degrees Fahrenheit.\u003c/p\u003e \u003cp\u003eAnnual population data by county was examined from two sources, United States Census Bureau (2023) and California Department of Finance (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGoogle (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) collected mobility data for weekdays from January 2020 through October 2022. Using the location of cell phones, estimates were made by county by day for the number of weekday hours at home. All values are expressed as percent change from the January 2019 baseline for the same day of the week, weekdays only.\u003c/p\u003e "},{"header":"METHOD","content":"\u003cp\u003eThis paper presents an original analysis of changes in California annual and monthly residential electricity consumption from 2017 through 2022. The trend is analyzed to provide a basis for forecasting future residential electricity consumption. Annual residential electricity consumption in California was calculated as the sum over counties and months for each year, 2017–2022. The years 2017–2019 were treated as pre-covid and 2020–2022 as covid years.\u003c/p\u003e\u003cp\u003eResidential electricity consumption for California by county and by utility service territory (sum over counties) was analyzed. Hot weather drives monthly variation in residential electricity consumption. Consumption typically increases with hotter temperatures (more cooling degree days). A regression was derived from monthly consumption and cooling degree days for each year, and for the two three-year periods (2017–2019 and 2020–2022). Three elements of change were identified and quantified: a) the intercept of the regression was interpreted as baseline (non-cooling) electricity; b) the slope (kWh/CDD) was analyzed as cooling; c) the change in slope after 2019 was interpreted as the change in electricity consumption related to hot weather. The change in slope is interpreted as primarily air conditioning but could be any electricity consumption associated with warmer temperatures.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe analysis provided the following results:\u003c/p\u003e\n\u003cp\u003e1) Annual residential energy consumption in California increased after 2019 and remained higher through 2022; California residential electricity consumption increased from 92,724 gigawatt hours (GWh) in 2019 to 102,945 GWh in 2020, an increase of 10,222 GWh (11.0%). The highest previous year was 2017 at 93,375 kWh. Population in California declined while residential electricity consumption increased.\u003c/p\u003e\n\u003cp\u003e2) Electricity consumption increased for non-cooling and cooling-related uses. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3) The amount of electricity consumed in comparably hot months has increased significantly.\u003c/p\u003e\n\u003cp\u003e4) Most of the increase in consumption is not associated with hot weather.\u003c/p\u003e\n\u003cp id=\"_Toc153180366\"\u003eANNUAL RESIDENTIAL ELECTRICITY CONSUMPTION IN CALIFORNIA INCREASED AFTER 2019\u003c/p\u003e\n\u003cp\u003eTable 1 shows that California residential electricity consumption increased in 2020 by 11.0% compared to 2019, remained 8.4% higher than 2019 in 2021, and increased to 11.7% higher than 2019 in 2022.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile one year may be unusual, a comparison was made of two three-year periods, 2017-2019 in comparison to 2020-2022 (bottom of table 1). The change from 2017-2019 to 2020-2022 was an increase of 29,211 GWh (average 9,737 GWh per year) or 10.5%. The trend resembles a step up in 2020 and continuing at a new higher level through 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. California Annual Residential GWh and CDD compared to 2019\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual Residential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in GWh from 2019 as %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalifornia population weighted CDD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in CDD from 2019 as %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2017 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e93,375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e19.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2018 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e91,760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e-1.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,312\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e5.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2019 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e92,724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2020 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e102,945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e11.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e26.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2021 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e100,536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e8.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2022 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e103,589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e11.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e1,418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e14.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange from 2017-2019 GWh as %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCalifornia population weighted CDD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in CDD from 2017-2019 as %\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2017-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e277,859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e4,038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e2020-2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e307,070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e10.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e4,259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20%;\"\u003e\n \u003cp\u003e5.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc153180367\"\u003eWARMER WEATHER DID NOT SIMPLY EXPLAIN HIGHER ANNUAL RESIDENTIAL ELECTRICITY CONSUMPTION\u003c/h2\u003e\n\u003cp\u003eHot weather leads to higher electricity consumption, particularly by air conditioners and fans to cool homes. Hot weather is the primary driver of differences in California residential electricity consumption from month to month.\u003c/p\u003e\n\u003cp\u003eCooling degree days (CDD) by county were weighted by county population to obtain California population weighted CDDs for each year. Population-weighted CDDs in 2020 (1,573) were higher than 2019 (1,243) by 26.6% and annual residential electricity consumption was higher by 11.0%. CDD were higher in 2020 than 2019, which accounts for some of the increase. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eComparisons of 2021 and 2022 to previous years in Table 1 show that changes in annual CDD do not simply explain changes in residential GWh. CDDs in 2021 (1,268) were similar to (2% higher than) CDDs in 2019 (1,243) and residential electricity consumption in 2021 (100,536 GWh) was 8.4% higher than in 2019 (92,724), an increase of 7,812 GWh. Population-weighted cooling degree days in 2022 (1,418) were 4.4% lower than 2017 (1,483), but residential electricity consumption in 2022 (103,589 GWh) was higher than 2017 (93,375) by 10,214 GWh (10.9% higher)\u003c/p\u003e\n\u003cp\u003eELECTRICITY CONSUMPTION INCREASED FOR NON-COOLING USES AND FOR COOLING\u003c/p\u003e\n\u003cp\u003eThe need for cooling is a significant explanatory variable for residential electricity consumption, explaining much of the month-to-month variation, with California monthly consumption ranging from about 6,000 to 12,000 GWh per month, highest in the summer months.\u003c/p\u003e\n\u003cp\u003eThe relative contributions of three factors were considered in explaining the difference between annual residential electricity consumption in covid (2020-2022) compared to baseline (2017-2019) periods: cooling degree days, change in slope of monthly GWh to CDD, and intercept.\u003c/p\u003e\n\u003cp\u003eFigure 1 illustrates a regression of monthly GWh against monthly CDD providing an intercept and a slope for each period. The intercept was interpreted as non-CDD-dependent GWh. Annual non-CDD-dependent GWh were calculated as 12 times the intercept. Annual CDD-dependent GWh were calculated as annual GWh minus non-CDD-dependent GWh.\u003c/p\u003e\n\u003cp\u003eFigure 2 shows California monthly residential electricity consumption and state-wide population-weighted cooling degree days for 2017 to 2022. To test whether a significant change has occurred, the data were combined for each three-year period. \u0026nbsp;Two linear regressions are shown, one for 2017 to 2019 (pre-covid) and one for 2020-2022 (covid). The relationship between CDD and residential electricity consumption changed after 2019 to a steeper slope of electricity consumption per CDD. Baseline (non-cooling) residential electricity consumption also increased (intercept).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis indicates that both non-cooling electricity (intercept) and cooling in response to temperatures (slope) remain higher than the historical trend observed through 2019. Based on a t-test, we can say with 95% certainty that California residential electricity consumption in 2017-2019 is lower than in 2020-2022. [1]\u003c/p\u003e\n\u003cp\u003eThe dependence of monthly residential electricity consumption on CDD was derived for each year, 2017 to 2022. \u0026nbsp;Figure 3 shows the data and linear regressions fit for each year.\u003c/p\u003e\n\u003cp\u003eAs noted previously, the range of cooling degree days is similar for most of the years, but the residential electricity consumption is higher in 2020, 2021, and 2022 than in previous years. \u0026nbsp;The linear regressions show that from 2017 to 2019, the slope GWh/CDD is 8.38 to 10.39, while for 2020-2022, the slope is 11.32 to 12.30. Monthly electricity consumption at the same CDD is higher after 2019.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, the intercepts have changed. \u0026nbsp;From 2017-2019, the intercepts ranged from 6,532 to 6,858 GWh, and from 2020-2022 the intercepts ranged from 7,094 to 7,178 GWh. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn 2019, California residential electricity consumption was 92,724 GWh. \u0026nbsp;Based on a linear regression of monthly residential electricity consumption to monthly CDD, the intercept is 6,858.5 GWh per month (times 12 = 82,302 GWh per year). The contribution dependent on CDD is 10,422 GWh per year (total annual GWh minus 12* intercept).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. CDD-dependent and non-CDD-dependent residential GWh for California, 2017-2022\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"359\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnnual Residential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-CDD dependent (12*intercept) GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCDD-dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2017 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e93,375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e78,709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e14,666\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2018 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e91,760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e78,390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e13,370\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2019 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e92,724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e82,302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e10,422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2020 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e102,945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e85,134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e17,811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2021 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e100,536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e85,504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e15,032\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2022 Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e103,589\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e86,143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e17,446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual Residential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual Non-CDD dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Annual CDD-dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2017-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e92,620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e79,800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e12,819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.3333%;\"\u003e\n \u003cp\u003e2020-2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 22.2222%;\"\u003e\n \u003cp\u003e102,357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 30.5556%;\"\u003e\n \u003cp\u003e85,594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.8889%;\"\u003e\n \u003cp\u003e16,763\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;Table 2 shows for years 2017-2022 the total GWh, non-CDD-dependent GWH (12*intercept), and the CDD-dependent GWh.\u003c/p\u003e\n\u003cp\u003eWhen comparing covid impact to baseline, the percent of total change was attributed to intercept (non-CDD-dependent GWh), cooling degree days (at baseline slope), and change in slope of GWh to CDD. \u0026nbsp;Table 3 shows that the change in intercept accounts for 60% of the total change (5,793 of 9,737 average annual GWh), change in slope accounts for 34% (3,944 GWh), and change in CDD accounts for 6% (619 GWh).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. California changes in residential electricity consumption in 2020-2022 compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 223px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 229px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in GWH in 2020-2022 compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 172px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of Total Change in 2020-2022 GWh compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual Residential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual Non-CDD dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage Annual CDD-dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual total change in GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual change in non-CDD-GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual change in GWh from change in CDD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual change in GWh from change in slope\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of total change from Non-CDD-dependent GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of total change from change in CDD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of total change from change in slope of GWh to CDD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2017-2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e92,620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e79,800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e12,819\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2020-2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e102,357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 53px;\"\u003e\n \u003cp\u003e85,594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;16,763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e9,737\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5,793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3,325\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e60%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e6%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e34%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp id=\"_Toc153180369\"\u003eCOOLING AND NON-COOLING ELECTRICITY BY UTILITY SERVICE AREA\u003c/p\u003e\n\u003cp\u003eMonthly county-level data for 2017 to 2022, including residential electricity consumption and population-weighted cooling degree days, was mapped onto major utility service areas. The correlation between monthly residential electricity consumption and monthly (population-weighted) cooling degree days was analyzed for each year, 2017-2021 individually, and for two three-year-combined sets, 2017-2019 (pre-covid) and 2020-2022 (covid impact).\u003c/p\u003e\n\u003cp\u003eFor all major utilities except SMUD, the covid impact increased both the intercept (non-CDD-dependent GWh) and the slope of GWh vs CDD. For SMUD, the intercept increased, but the slope is not changed. For LADWP, although the slope increased, the number of CDD was 10% lower in 2020-2022 than in 2017-2019.\u003c/p\u003e\n\u003cp\u003eResults differed among the utility service territories.[2] Comparing 2020-2022 (covid impact) to 2017-2019 (baseline), Table 4 shows that the covid impact was an annual average increase for each utility ranging from +5.3 to +12.8%. The intercept (non-CDD-dependent GWh) contributed 42 to 65% of this change, the change in slope of GWh to CDD contributed -0.5 to 48.9% of the total change and change in CDD contributed -13 to +58%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Changes in residential electricity in 2020-2022 compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020-2022\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eResidential GWh\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 227px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChange in GWh in 2020-2022 compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePercent of total change in 2020-2022 GWh compared to 2017-2019 (pre-covid)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage annual Residential GWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage annual Non-CDD dependent GWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage Annual CDD-dependent GWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAverage annual total change in GWh\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage annual change in non-CDD-GWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage annual change in GWh from change in CDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eAverage annual change in GWh from change in slope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePercent of total change from Non-CDD-dependent GWh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePercent of total change from change in CDD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePercent of total change from change in slope of GWh to CDD\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003ePG\u0026amp;E\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e34,449\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e30,751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 3,698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e2,846 (+9%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e739\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eSCE\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e40,046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e31,002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e9,044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e4,547\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(+12.8%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1,960\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e52.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eSDGE\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7,898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e7,002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; 896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e695 (+9.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e65.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e30.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003eSMUD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e5,059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e4,234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp; 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Lockdowns in response to covid-19 in April 2020 increased the number of hours at home by about 20% (simple average across counties). Hours-at-home decreased over time during 2020-2022, with upticks during periods of higher levels of covid-19 (e.g., January 2021, January 2022, and July 2022).\u003c/p\u003e\n\u003cp\u003eAfter the initial lockdown, hours-at-home generally declined until 2022, with some upticks in response to higher covid levels, particularly in January 2021, January 2022, and July 2022.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAttempts to correlate hours at home with monthly residential energy consumption for selected counties failed to show a high correlation. \u0026nbsp;Figures 5 and 6 show examples for Los Angeles and Alameda Counties, respectively. The large variations in residential electricity consumption from month to month are correlated with weather (e.g., cooling degree days), not with hours-at-home.\u003c/p\u003e\n\u003cp\u003eFigure 7 shows changes expressed as percent change from 2019 for California state-wide annual residential electricity consumption (GWh), weekday hours-at-home, and population. California residential electricity increased after 2019 and has remained higher in 2021 and 2022, while population has declined. Hours at home increased in 2020 and has declined in 2021 and 2022.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Mobility data documents hours-at-home by county by month for 2020-2022. \u0026nbsp;Residential electricity consumption increased in 2020, mostly in line with hours-at-home. Hours-at-home peaked in early 2020, generally declined until 2022, with upticks during surges of covid cases. \u0026nbsp;In 2022, while hours-at-home continued to move back toward 2019 values, residential electricity consumption remained high.\u003c/p\u003e\n\u003cp\u003e[1] The t stat is -2.246 for a one-tailed test with 35 observations.\u003c/p\u003e\n\u003cp\u003e[2] PG\u0026amp;E is Pacific Gas and Electric. SCE is Southern California Edison. SDGE is San Diego Gas and Electric. SMUD is Sacramento Municipal Utility District. LADWP is Los Angeles Department of Water and Power.\u003c/p\u003e"},{"header":"CONCLUSIONS AND DISCUSSION","content":"\u003cp\u003eResidential electricity consumption increased in 2020 and remained higher than historical levels in 2021 and 2022. Both non-CDD-related and CDD-related electricity increased and remains higher. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMore research is needed to allocate these changes to end uses, that is, to determine whether changes are due to conditioned space (such as conversions to office space), specific types of equipment (such as air cleaners or home office equipment) or to usage behavior (such as more cooling hours or lower temperature setpoints).\u003c/p\u003e\n\u003cp\u003eThe implication is that future California residential electricity consumption is likely to remain higher than historical trends until 2019 would have suggested. As data on residential electricity consumption continues to be accumulated in future, analysis should continue to evaluate the degree to which higher residential electricity consumption persists or whether it is returning to previous levels.\u003c/p\u003e\n\u003cp\u003eIncreases in hours-at-home on weekdays, based on mobility data, are not well correlated with the changes in residential monthly electricity consumption at the county level for the period 2020 to 2022. The mobility data did not include weekends. The analysis to date was not able to establish the use of mobility data (weekday hours-at-home) as a good predictor of residential electricity consumption. The changes in residential electricity consumption initiated during covid are persisting, even as workers return to work or to hybrid schedules (working some days at home).\u003c/p\u003e\n\u003cp id=\"_Toc153180378\"\u003eLIMITATIONS AND FUTURE WORK\u003c/p\u003e\n\u003cp\u003eThis study was limited to California and its counties.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study was limited to total residential electricity. Future work can be directed to more disaggregated analysis. \u0026nbsp;Additional research on load profiles and end uses (equipment saturations and usage behaviors) since 2019 is recommended to allocate the changes to end uses and times of day. Continued tracking of load profiles and end use consumption is recommended to evaluate any potential trend since 2020 that might provide insight into future residential electricity consumption in California.\u003c/p\u003e\n\u003cp\u003eThis research could include a) Longitudinal studies of a sample of households having hourly or finer consumption data from 2019 to 2022 to determine changes in electricity usage profiles; b) Surveys and behavioral studies to inform estimates of changes in usage and hourly profiles by end use; c) Future work could examine residential natural gas consumption.\u003c/p\u003e\n\u003cp\u003eThe mobility data cited here regarding weekday hours-at-home was only available from March 2020 through October 2022. \u0026nbsp;A source of mobility data that continues over time could be used as an indicator of return to some behavior to 2019 levels, although direct studies of actual behaviors may provide more insight.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFUNDING DECLARATION:\u003c/p\u003e\n\u003cp\u003eThis work was conducted under subcontract to Aspen Environmental Group (Subcontract No. 1980-000-03) for California Energy Commission (CEC) Work Authorization # 1981.003 in support of subtask 4, Calibration, specifically, calibration for covid impacts after 2019.\u003c/p\u003e\n\u003cp\u003eCONFLICT OF INTEREST STATEMENT:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthor Contribution\u003c/p\u003e\n\u003cp\u003eJ.M. designed and conducted the analysis and wrote the paper. J.L. contributed data, prepared one figure, and reviewed the paper.\u003c/p\u003e\n\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eThis work was conducted under subcontract to Aspen Environmental Group (Subcontract No. 1980-000-03) for California Energy Commission (CEC) Work Authorization # 1981.003 in support of subtask 4, Calibration, specifically, calibration for covid impacts after 2019. We want to thank Taylor Harms and other CEC staff for support, data, discussion, and review of this work.\u003c/p\u003e\n\u003cp\u003eData Availability\u003c/p\u003e\n\u003cp\u003eThe author confirms that all data generated or analysed during this study are included in this published article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBielecki, S.; Skoczkowski, T.; Sobczak, L.; Buchoski, J.; Macia˛g, Ł.; Dukat, P. (2021), Impact of the Lockdown during the COVID-19 Pandemic on Electricity Use by Residential Users. \u003cem\u003eEnergies\u003c/em\u003e, 14, 980. https://doi.org/10.3390/en14040980\u003c/li\u003e\n \u003cli\u003eCalifornia Department of Finance, (2023), CA Total Population. July 1 Estimates and Projections, https://dof.ca.gov/forecasting/demographics/estimates/ Last Updated 7/19/2023.\u003c/li\u003e\n \u003cli\u003eCalifornia Energy Commission, (2024), 2024 Integrated Energy Policy Report. 2024 Integrated Energy Policy Report Update\u003c/li\u003e\n \u003cli\u003eCicala,S. (2023) JUE Insight: Powering work from home, \u003cem\u003eJournal of Urban Economics\u003c/em\u003e 133, 103474. Https://doi.org/10.1016/j.jue.2022.103474\u003c/li\u003e\n \u003cli\u003eDebnath, R.; Bardhan, R.; Misra, A; Hong, Tianzhen; Rozite, V.; Ramage, M.H. (2022), Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian Mixture models, \u003cem\u003eEnergy Policy\u003c/em\u003e 164, 112886. https://www.sciencedirect.com/science/article/pii/S0301421522001112\u003c/li\u003e\n \u003cli\u003eDu, M.; Ruan, J.; Zhang, L.; Nui, M.; Zhang, Z.; Xia, L.; Qian, S.; Chen, C. (2024), China\u0026rsquo;s local level monthly residential electricity power consumption monitoring. \u003cem\u003eApplied Energy\u003c/em\u003e 359, 122658 https://www.sciencedirect.com/science/article/abs/pii/S0306261924000412#:~:text=\u003cbr\u003eAs%20a%20fast%2Ddeveloping%20country,%25)%20in%202020%20%5B14%5D.\u003c/li\u003e\n \u003cli\u003eFarrow H.(2020), Commercial down v residential up: COVID-19\u0026rsquo;s electricity impact. \u003cem\u003eEnergy Networks Australia\u003c/em\u003e. https://www.energynetworks.com.au/news/ energy-insider/2020-energy-insider/commercial-down-v-residential-up-covid-19s-electricity-impact/\u003c/li\u003e\n \u003cli\u003eGarcia, S., Parajo, A., Personal, E., Guerrero, J.I.; Biscarri, F.; and Leon, C. (2021), A retrospective analysis of the impact of the COVID-19 restrictions on energy consumption at a disaggregated level, \u003cem\u003eApplied Energy\u003c/em\u003e 287, 116547. https://doi.org/10/1016/j.appenergy.2021.116547\u003c/li\u003e\n \u003cli\u003eGausden G. (2020), Home electricity consumption now peaks at 1pm while smart meter data suggests people are having early nights AND late mornings. Article in \u003cem\u003eThis is Money\u003c/em\u003e. https://www.thisismoney.co.uk/money/bills/article-8224837/Energy-usage-risen-17-lockdown-reveal-tips-bills-down.html\u003c/li\u003e\n \u003cli\u003eGoogle 2023. Google LLC, Google COVID-19 Community Mobility Reports.\u003cbr\u003ehttps://www.google.com/covid19/mobility/ Accessed: July 27, 2023.\u003c/li\u003e\n \u003cli\u003eHarms, T., (2023). Personal communication, Taylor Harms, California Energy Commission, August 8, 2023. QFER data in Dropbox. Monthly residential GWh by county 1985-2022. Consumption data is publicly available at Electricity Consumption by County\u003c/li\u003e\n \u003cli\u003eKawka, E. and Cetin, K.(2021), Impacts of COVID-19 on residential building energy use and performance, \u003cem\u003eBuilding and Environment\u003c/em\u003e 205, 108200. https://doi.org/10.1016/j.buildenv.2021.108200\u003c/li\u003e\n \u003cli\u003eKrarti, M. and Aldubyan, M. (2021), Review analysis of COVID-19 impact on electricity demand for residential buildings\u003cem\u003e. Renewable and Sustainable Energy Reviews\u003c/em\u003e 143, 110888. https://doi.org/10.1016/j.rser.2021.110888\u003c/li\u003e\n \u003cli\u003eSavills News (2020), COVID-19 restrictions changing the daily patterns of energy consumption. https://www.savills.us/insight-and-opinion/savills-news/299070/covid-19- restrictions-changing-the-daily-patterns-of-energy-consumption\u003c/li\u003e\n \u003cli\u003eUnited States Census Bureau, County Population Totals and Components of Change: 2020-2022. https://www.census.gov/data/tables/time-series/demo/popest/2020s-counties-total.html\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"residential electricity, covid, cooling","lastPublishedDoi":"10.21203/rs.3.rs-6474769/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6474769/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn response to the covid pandemic, residential electricity use changed in 2020. In California, government-mandated lockdowns closed businesses and resulted in many people spending more time at home. In 2021 and 2022, most people returned to work, as evidenced by location tracking of cell phones. This paper describes analysis of monthly residential electricity consumption at the county level for California from 2017 to 2022. Results show that residential electricity consumption increased in 2020 and did not return to 2019 levels in either 2021 or 2022. Since hot weather is the primary driver of change in monthly residential electricity use in California, the dependence of residential electricity use on cooling degree days was analyzed. Warmer weather does not explain the increase. Results show that both non-cooling (\u0026ldquo;baseline\u0026rdquo;) electricity use increased, perhaps due to new equipment in homes, and that hot weather electricity use also increased compared to historical years. Both effects were observed for the service territories of most utilities in California to varying degrees. Future research will examine possible explanations, including conversion of existing or new floorspace in homes into office space, additional equipment (air cleaners, office equipment), and behavioral changes (hours of use, temperature set-points).\u003c/p\u003e","manuscriptTitle":"Persistent impacts of covid pandemic on residential electricity consumption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 06:02:06","doi":"10.21203/rs.3.rs-6474769/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"916e5abc-045d-46c9-a34b-81d123f8867b","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-18T05:24:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 06:02:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6474769","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6474769","identity":"rs-6474769","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}