Changes in energy consumption according to building use type under COVID-19 pandemic in South Korea

Co-occurrence of urban heat and the COVID-19: Impacts, drivers, methods, and implications for the post-pandemic era

Cities, the main place of human settlements, are under various mega challenges such as climate change, population increase, economic growth, urbanization, and pandemic diseases, and such challenges are mostly interlinked. Urban heat, due to heatwaves and heat islands, is the combined effect of climate change and urbanization. The COVID-19 is found to be a critical intervention of urban heat. However, the interrelationship between COVID-19 and urban heat has not been fully understood, constraining urban planning and design actions for improving the resilience to the dual impacts of heat and the pandemic. To close this research gap, this paper conducted a review on the co-occurrence of urban heat and the COVID-19 pandemic for a better understanding of their synergies, conflicts or trade-offs. The research involves a systematic review of urban temperature anomalies, variations in air pollutant concentrations, unbalanced energy development, and thermal health risks during the pandemic lockdown. In addition, this paper further explored data sources and analytical methods adopted to screen and identify the interventions of COVID-19 to urban heat. Overall, this paper is of significance for understanding the impact of COVID-19 on urban heat and provides a reference for coping with urban heat and the pandemic simultaneously. The world is witnessing the co-existence of heat and the pandemic, even in the post-pandemic era. This study can enlighten city managers, planners, the public, and researchers to collaborate for constructing a robust and resilient urban system for dealing with more than one challenges.

Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm

COVID-19 has affected energy consumption and production pattern in various sectors in both rural and urban areas. Consequently, energy demand has increased. Therefore, most health care centers report a shortage of energy, particularly during the summer seasons. Therefore, integrating renewable energies into hospitals is a promising method that can generate electricity demand reliably and emits less CO2. In this research paper, a hybrid renewable energy system (HRES) with hydrogen energy storage is simulated to cover the energy demand of sections and wards of a hospital that dealt with COVID-19 patients. Produced Oxygen from the hydrogen storage system is captured and stored in medical capsules to generate the oxygen demand for the patients. Results indicate that 29.64% of the annual consumed energy is utilized in COVID-19 sections. Afterward, modeled system has been optimized with a neural network-genetic algorithm to compute the optimum amount of the demand power from the grid, CO2 emission, oxygen capsules, and cost rate. Results determine that by having 976 PV panels, 179 kW fuel cell, and 171.2 kW electrolyzer, annual CO2 emission is 315.8 tons and 67,833 filled medical oxygen capsules can be achieved. The cost rate and demand electricity from the grid for the described system configuration are 469.07 MWh/year and 18.930 EUR/hr, respectively.

Impact of the COVID-19 on electricity consumption of open university campus buildings - The case of Twente University in the Netherlands

Since the COVID-19 outbreak, the restrictive policies enacted by countries in response to the epidemic have led to changes in the movement of people in public places, which has had a direct impact on the use and energy consumption of various public buildings. This study was based on electricity consumption data for 25 on-campus public buildings at 1-hour intervals between January 2020 and June 2022 at Tewnte University in the Netherlands, and after the data were climate-corrected by multiple regression analysis, the changes in EU and EUI for various types of buildings were compared for different restriction periods using ANOVA, LSD and t-tests. And additionally, further analyzed the changes and reasons for the electricity consumption of various public buildings on campus and customers' electricity consumption behavior in a period of time after the lifting of the epidemic restriction policy. The results of ANOVA analysis show that the restriction policy has a significant effect on teaching, sports, and cultural buildings, and the electricity intensity of the three types of buildings is reduced by 0.28, 0.09, and 0.07 kwh/m²/day respectively under the strict restriction policy; The t-test results show that during the restriction period, all building types, except for living and academic buildings, show a significant decreasing trend, with the teaching buildings having the greatest energy saving potential, with an average daily EU reduction of 1088kwh/day and an EUI reduction of 0.075kwh/ m²/day. The above findings provide a case study of a complete cycle of energy consumption changes in university buildings under similar epidemic restriction policies before and after the epidemic restriction, and inform the electricity allocation policies of university and government energy management authorities.

Is Europe on the Way to Sustainable Development? Compatibility of Green Environment, Economic Growth, and Circular Economy Issues

The challenges imposed by climate change and the limited nature of resources generate paradigm shifts at the level of economic, social, and environmental policies and strategies. Promoting the principles of sustainable development and the circular economy is a priority worldwide. Thus, the motivation of this research is to explore the European countries' path toward sustainable development by analysing the relationship between green environment, economic growth, and circular economy issues. In order to explore this relationship in the case of European countries, the analysis takes into consideration specific variables: final energy consumption, GDP, capital gross fixed capital formation, greenhouse gas emissions, SOx emissions, NOx emissions, and generation of municipal waste per capita. This study is focused on the period 2009-2020 for 31 European countries, with data being provided by Eurostat and World Bank databases. The panel data analysis was used in order to examine the relationship between a green environment, economic growth and a circular economy. The results of the study suggest that gross fixed capital formation and total greenhouse gas emissions lead to decreasing generation of municipal waste; instead, final energy consumption, GDP, SOx emissions and NOx emissions generate an increase in the generation of municipal waste. The novelty of our paper consists of associating green environment, economic growth, and circular economy in the case of European countries, the results allowing the proposal of economic policy measures to favor the green transition process considering the potential of the circular economy.

A robust and resilience machine learning for forecasting agri-food production

This research proposes a new framework for agri-food capacity production by considering resiliency and robustness and paying attention to disruption and risk for the first time. It is applied robust stochastic optimization by adding robustness to the constraint's objective function and resiliency situation. This research minimizes the mean absolute deviation and coefficient of standard deviation errors by linear function in the agri-food capacity production. This study suggests agri-food managers and decision-makers use this mathematical method to forecast and improve production management. The results of this research lead to better decision-making and are compared with other sine functions. The main model's Robust and Resiliency Mean Absolute Deviation (RRMAD) value is 1.28% lower than other sine-type functions. The conservativity coefficient, confidence level, weight factor, resiliency coefficient, and probability of the scenario vary. The main model's RRMAD value is 1.28% lower than other sine-type functions. Growing the weight factor will result in an increase in RRMAD and a smooth decline in R-squared. Additionally, as the resilience coefficient rises, the RRMAD function increases while the R-squared declines. By altering the probability of the scenario, the RRMAD function drops, and the R-squared goes up.

Investigating the impacts of COVID-19 lockdown on air quality, surface Urban Heat Island, air temperature and lighting energy consumption in City of Melbourne

The COVID-19 pandemic has threatened city economies and residents' public health and quality of life. Similar to most cities, Melbourne imposed extreme preventive lockdown measures to address this situation. It would be reasonable to assume that during the two phases of lockdowns, in autumn (March) and winter (June to August) 2020, air quality parameters, air temperature, ^{Surface Urban Heat Island} (SUHI), and lighting energy consumption most likely increased. As such, to test this assumption, Sentinel 5, ERA-5 LAND, Sentinel 1 and 2, NASA SRTM, MODIS Aqua and Terra, and VIIRS satellite imageries are utilized to investigate the alterations of NO₂, SO₂, CO, ^{UV Aerosol Index} (UAI), air temperature, SUHI, and lighting energy consumption factors in the City of Melbourne. Furthermore, satellite imageries of SentiThe results indicate that the change rates of NO₂ (1.17 mol/m²) and CO (1.64 mol/m²) factors were positive. Further, the nighttime SUHI values increased by approximately 0.417 °C during the winter phase of the lockdown, while during the summer phase of the lockdown, the largest negative change rate was in NO₂ (−100.40 mol/m²). By contrast, the largest positive change rate was in SO₂ and SUHI at night. The SO₂ values increased from very low to 330 μm mol/m^2, and the SUHI nighttime values increased by approximately 4.8 °C. From the spatial point of view, this study also shows how the effects on such parameters shifted based on the urban form and land types across the City of Melbourne by using satellite data as a significant resource to analyze the spatial coverage of these factors. The findings of this study demonstrate how air quality factors, SUHI, air temperature, and lighting energy consumption changed from pre-lockdown (2019) to lockdown (2020), offering valuable insights regarding practices for managing SUHI, lighting energy consumption, and air pollution.

Effect of Travel Expenditure on Life Satisfaction for Middle-Aged and Older Adults in Korea: Moderating Effect of COVID-19 Pandemic

The aim of this research was to examine the effects of travel expenditures on life satisfaction in the context of the COVID-19 pandemic. For the research, a curvilinear relationship was established between life satisfaction and travel expenditures that was then compared between 2018 and 2020. The study subjects were middle-aged and older adults who completed the 2018 and 2020 waves of the Korean Longitudinal Study of Aging. Demographic, travel expenditure, and life satisfaction data were collected, and quadratic regression analysis was conducted to examine the effects of travel expenditures on life satisfaction before and during the COVID-19 pandemic. The first-order condition was computed to determine the optimal level of travel expenditures to maximize life satisfaction, and the results exhibit that the utility of travel expenditure decreased during the COVID-19 pandemic.

Microplastic: A particulate matter(PM) generated by deterioration of building materials

Particulate matter (PM), an inhalable material, is generated from various sources, including building materials. To maintain indoor air quality, it is necessary to analyze harmful substances and establish a method for their remediation. The purpose of this study is to identify the particles generated during the deterioration of building materials and analyze the composition of fine dust particles with respect to the degree of deterioration. The concentration of particles generated was analyzed using an SPS30 PM sensor in the built chamber. PM10 and PM2.5 levels of the maximum of 41.95 mg/m³ and 20.63 mg/m³, respectively, were generated from the tested building materials. The components of the collected PM were carbon, hydrogen, and silicon, among others, which are high-molecular-weight compounds. Particles of size 2.5 µm or less were detected, and the possibility of generating nanoplastics was investigated.

Electricity consumption variation of public buildings in response to COVID-19 restriction and easing policies: A case study in Scotland, U.K

A growing number of studies have showed energy demand changes during COVID-19; this study aims to further disclose the impact of the restriction and easing policies on the energy consumption of public buildings where occupants' usage and activities are regulated in response to the pandemic. This study analyzes half-hourly electricity consumption data of 35 public buildings covering 6 building types in the Perth and Kinross Council area in Scotland, U.K., over the span of 2020 and 2021. The results show that the restriction has a greater impact on the electricity reduction in the first year of the pandemic than that in the second year. In response to the restriction, the electricity use intensity of all public buildings reduces significantly (p < 0.001) except office buildings with no significant reduction (p > 0.05); secondary schools have the highest electricity consumption reduction (275.04 kwh/day), while museums have the lowest reduction (58.62 kwh/day). In addition, the electricity consumption and electricity use intensity of museum, library and school buildings are inversely proportional to the restriction intensity, while this is opposite for office buildings. Combing restriction intensity and mobility data, this research reveals the different impacts of the restriction policies on the electricity consumption of public buildings during the pandemic, which reflects people's changing attitudes and behaviors towards COVID-19. The results provide a reference basis for energy management to develop more realistic energy demand policies based on public building types and to optimize the electricity supply load and energy profile during the COVID-19 pandemic.

Photovoltaic rooftop's contribution to improve building-level energy resilience during COVID-19 work-from-home arrangement

The COVID-19 pandemic has introduced opportunities for more research in resilience as globally cities experienced lock-down, causing change to conventional energy consumption pattern especially in the residential sector. This study aims to quantify the increased energy demand during work-from-home arrangement, using high-rise public residential buildings in Hong Kong, where its government announced work-from-home arrangement four times in 2020. Building energy modellings were conducted to compare the total energy demand of residential units during normal and work-from-home arrangements, followed by validation against peer models and empirical data. A 9% residential energy demand increase was demonstrated, hence additional energy supply became desirable for the sake of resilience. This study assesses the possibility to leverage photovoltaic rooftop to supplement the increased energy demand. The photovoltaics' potential contribution was estimated by solar energy simulation and evaluated in terms of the capability to utilize its generation output to supplement the additional energy demand. During the four work-from-home periods, it was shown that a photovoltaic system could have supplemented 6.8% - 11% of the increased energy demand, mainly subject to the air-conditioning operation and solar generation. These findings are valuable to safeguard energy resilience in upcoming grid planning and operation.

Environmental Effects of the COVID-19 Pandemic: The Experience of Bogotá, 2020

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced activities and protection policy measures in cities. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism and industrial production stopped normal life, transportation, etc. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogotá, Colombia.

Tracing the Impact Pathways of COVID-19 on Tourism and Developing Strategies for Resilience and Adaptation in Iran

The COVID-19 epidemic has caused unprecedented impacts on the travel and tourism industry. The current study traced the impacts of COVID-19 on tourism in Iran using an “Impact Pathway (IP)” approach to identify impacts and possible mitigation strategies. The results illustrate two main impact pathways: negative impacts along the economic-institutional and socio-cultural dimensions, and positive impacts along the physical-environmental dimension. Using SWOT (strengths, weaknesses, opportunities, and threats) and ANP (analytic network process) models, we identified defensive and review strategies as optimal for increasing resilience against the impacts of COVID-19. These strategies control the threats and weaknesses of negative impacts and enhance the opportunities and strengths emerging from the COVID-19 pandemic for tourism. We use this information to identify optimal strategies for dealing with the impacts of this crisis on tourism. Most prominently among them is the development of an integrated management system that improves the coordination of the response of local government to crisis and that better orchestrates the combined efforts and integration of non-governmental organizations.

How natural disasters affect carbon emissions: the global case

The outbreak of the COVID-19 pandemic has once again made the impacts of natural disasters a hot topic in academia. The environmental impacts of natural disasters, however, remain unsettled in the existing literature. This study aims to investigate the impact of natural disasters on CO₂ emissions. For this purpose, we employ a panel dataset covering 138 countries over the period 1990-2018 and two dynamic panel estimation methods. Then, considering the differences in CO₂ emissions across various countries, we run a panel quantile regression to examine the asymmetry in the nexus between natural disasters and CO₂ emissions. We also discuss the mediating effects of energy consumption between natural disasters and CO₂ emissions. After conducting a series of robustness checks, we confirm that our results are stable and convincing. The empirical results indicate that natural disasters significantly reduce CO₂ emissions. Nevertheless, the impact of natural disasters on CO₂ emissions is asymmetric across different quantiles of CO₂ emissions. Furthermore, the technology level serves as an important moderating factor between natural disasters and CO₂ emissions. The mediating effect results reveal that natural disasters not only directly reduce CO₂ emissions but also indirectly promote carbon reduction by restraining energy consumption. Finally, several policy implications are provided to reduce CO₂ emissions and the damage caused by natural disasters.

Investigation on household energy consumption of urban residential buildings in major cities of Indonesia during COVID-19 pandemic

The implementation of the movement control order (MCO) to curb the spread of the 2019 novel corona virus disease (COVID-19) have influenced household energy consumption patterns around the world. This study aims to investigate household energy consumption of urban residential buildings in major cities of Indonesia during COVID-19 pandemic. Three representative major cities of Indonesia were selected to investigate detailed information about household appliances and gas consumption through face-to-face interviews in 2021 (n = 311). The factors affecting household energy consumption were investigated by multiple regression analysis. The results showed that, overall, the average annual energy consumption of all samples during pandemic was approximately 23.5 GJ, 3.0 GJ larger than before pandemic. The difference was primarily attributed to the use of air conditioning and cooking. The statistical analysis clearly indicated that the increase in household income (low-to high-cost houses), which would increase household size and number of appliances including air conditioning, thus increased total household energy consumption. We recommended the following potential energy-saving strategies for urban houses in Indonesia: (a) control the number of family members, (b) use more energy efficiency standards for electrical appliances and (c) encourage energy-saving lifestyles, particularly to younger adults by adopting passive cooling techniques (window opening) whereever possible.

A three-year dataset supporting research on building energy management and occupancy analytics

This paper presents the curation of a monitored dataset from an office building constructed in 2015 in Berkeley, California. The dataset includes whole-building and end-use energy consumption, HVAC system operating conditions, indoor and outdoor environmental parameters, as well as occupant counts. The data were collected during a period of three years from more than 300 sensors and meters on two office floors (each 2,325 m2) of the building. A three-step data curation strategy is applied to transform the raw data into research-grade data: (1) cleaning the raw data to detect and adjust the outlier values and fill the data gaps; (2) creating the metadata model of the building systems and data points using the Brick schema; and (3) representing the metadata of the dataset using a semantic JSON schema. This dataset can be used in various applications-building energy benchmarking, load shape analysis, energy prediction, occupancy prediction and analytics, and HVAC controls-to improve the understanding and efficiency of building operations for reducing energy use, energy costs, and carbon emissions.

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

The COVID-19 pandemic has significantly affected people's behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre- and post-COVID-19 pandemic times. The weekend usage patterns look similar pre- and post-COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

The Energy Efficiency Post-COVID-19 in China’s Office Buildings

China promptly took the leading step to mitigate the spread of COVID-19, producing the first scientific guidelines assuming health above energy consumption and significantly changing HVAC/AHU operation. The research intended to fulfill the gap by measuring the impact of the guidelines on energy use intensity, CO2 emissions, and energy operation costs related to workplaces. The guidelines are long-term sector and industry trends following occupants’ health and safety concerns, and today they are applied to nursing homes. The research extended the study to post-COVID-19 scenarios by crossing those settings with published reports on telework predictions. The methodology resorts to Building Energy Simulation software to assess the Chinese standard large office building on 8 climate zones and 17 subzones between pre- and post-COVID-19 scenarios under those guidelines. The outcomes suggest an upward trend in energy use intensity (11.70–12.46%), CO2 emissions (11.13–11.76%), and costs (9.37–9.89%) for buildings located in “warm/mixed” to “subarctic” climates, especially in colder regions with high heating demands. On the other hand, the figures for “very hot” to “hot/warm” climates lower the energy use intensity (14.76–15.47%), CO2 emissions (9%), and costs (9.64–9.77%).

Comparison of Indoor Environment and Energy Consumption before and after Spread of COVID-19 in Schools in Japanese Cold-Climate Region

A report released by the WHO indicates that aerosols from infected people are one of the major sources of the spread of COVID-19. Therefore, as the COVID-19 infection caused by the SARS-CoV-2 virus spreads, it has become necessary to reconsider the design and operation of buildings. Inside school buildings in cold regions, not only is it not easy to increase ventilation during the winter, but it may also be difficult for students to attend classes while wearing masks during the summer because such buildings are not equipped with air-conditioning systems. In short, school buildings in cold climates have more problems than those in warm climates. We report on the results of indoor environmental measurement using our developed CO2-concentration meters, a questionnaire survey on students’ feeling of being hot or cold (i.e., ‘thermal sensation’), and a comparison of energy consumption before and after the spread of COVID-19 infection in schools in Sapporo, Japan, a cold-climate area. The results indicate that (1) more than 70% of the students participated in window ventilation by the CO2 meter, and (2) a relatively good indoor environment was maintained through the efforts of teachers and students. However, we also found that (1) 90% of the students felt hot in summer and (2) 40% felt cold in winter, (3) energy efficiency worsened by 7% due to increased ventilation, and (4) air quality was not as clean as desired during the coldest months of the year. Therefore, investment in insulation and air conditioning systems for school buildings is needed.

Assessing the impact of the COVID-19 lockdown on the energy consumption of university buildings

Exceptional pandemic lockdown measures enabled singular experiments such as analysing the energy consumption of vacant buildings. This paper assesses the impact of the COVID-19 lockdown on the energy use of academic buildings. For this purpose, weather-adjusted energy use was compared before and during the lockdown, including different levels of lockdown restrictions. Results obtained for the 83 academic buildings of Universitat Politècnica de Catalunya - Barcelona Tech (UPC) reveal that the avoided energy consumption amounted to over 4.3 GWh during the post-pandemic year. However, the results indicate that academic buildings were still using approximately 46.9% of their typical energy consumption during strict lockdown. This revelation emphasizes the high environmental burden of buildings, regardless of whether they are occupied.

Office buildings occupancy analysis and prediction associated with the impact of the COVID-19 pandemic

Buildings' occupancy is one of the important factors causing the energy performance and sustainability gap in buildings. Better occupancy prediction decreases this gap both in the design stage and in the use phase of the building. Machine learning-based models proved to be very accurate and fast for occupancy prediction when buildings are exploited under normal conditions. Meanwhile, during the Covid-19 pandemic occupancy of the offices has dramatically changed. The study presents 2 office buildings' long-term monitoring results for different periods of the pandemic. It aims to analyse actual occupancies during the pandemic and its influence on the ELM (Extreme Learning Machine) based occupancy-forecasting models' reliability. The results show much lower actual occupancies in the offices than given in standards and methodologies; it is still low even when quarantines are cancelled. Average peak occupancy within the whole measured period is: for Building A - 12-20% and for Building B - 2-23%. The daily occupancy schedules differ for both offices as they belong to different industries. ELM-SA model has shown low accuracies during pandemic periods as a result of lower occupancies - R2 = 0.27-0.56.

Integrative Smart Grids’ Assessment System

The COVID-19 pandemic has significantly affected the energy sector. The new behavior of industrial and non-commercial consumers changes the energy consumption model. In addition, the constraints associated with the coronavirus crisis have led to environmental effects from declining economic activity. The research is based on evidence from around the world showing significant reductions in emissions and improved air quality. This situation requires rethinking the energy development strategy, particularly the construction of smart grids as a leading direction of energy development. Evaluating the efficiency of smart grids is a vital tool for disseminating successful experience in improving their management. This paper proposes an approach to a comprehensive assessment of smart grids based on a comparative analysis of existing methods, taking into account the changes that need to be considered after the experience gained from the COVID-19 pandemic. The approach provides an accurate set of efficiency indicators for assessing smart grids to account for the direct and indirect effects of smart grids’ implementation. This evaluation approach can be helpful to policymakers in developing energy efficiency programs and implementing energy policy.

Household Water and Energy Consumption Changes during COVID-19 Pandemic Lockdowns: Cases of the Kazakhstani Cities of Almaty, Shymkent, and Atyrau

The COVID-19 pandemic has changed the daily behaviors of people by forcing them to spend the majority of their time in their residences, particularly during social distancing measures. The increased time spent at home is expected to influence, among other things, the daily consumption of utilities: specifically, water and energy. A prolonged presence of residents at home during COVID-19 lockdowns might increase strain on water and energy resources, which are mostly from non-renewable sources in several countries, including Kazakhstan; however, such potentially important effects have not yet been studied for the country. The present research aims to evaluate how the COVID-19 pandemic lockdowns have affected the water and energy consumption in residential housings in cities of varying sizes in Kazakhstan, providing a novel understanding of the effect of pandemic lockdowns on household energy and water consumption. Energy and water consumption data of Almaty, Shymkent, and Atyrau have been first obtained from the local service companies, and then, the usage behavior was analyzed for the periods before, during, and after the COVID-19 pandemic lockdown. After, statistical tests were conducted to check the hypotheses regarding the effect of COVID-19 pandemic lockdowns on the consumption of energy and water. The findings indicate that residential energy and water consumption increased during the lockdown periods in large and medium cities. Nevertheless, this growth is not highly significant compared to similar non-pandemic timeframes. This result could indicate a particular risk for sustainable resources consumption and put pressure on the supply companies. Moreover, in case of further lockdown measures, current building systems are at risk of increased pressure, and eventually, of failure.

Impact of the COVID-19 Pandemic to the Sustainability of the Energy Sector

In order to control the COVID-19 pandemic, the governments of the world started to implement measures regarding social distance and social contacts, including closures of cities, work and study relocations, and work suspension. The epidemical situation and the lockdown of the economy by governments in various countries caused changes in production, changes in the habits of energy consumers and other energy-related changes. This article analyses the impact of the global pandemic on the energy sector and the relationship with the progress to the sustainability of the energy sector. The systematic literature review was performed in the Web of Science (WoS) database. The research follows recommendations of the SALSA (Search, Appraisal, Synthesis and Analysis) and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approaches. A total of 113 relevant articles were selected for the analysis. All selected articles were categorized according to their application and impact areas. The five main impact areas of the COVID-19 pandemic to the sustainability of the energy sector were identified: consumption and energy demand; air pollution; investments in renewable energy; energy poverty; and energy system flexibility. Based on the current research findings and perception of the problem, the main insights for future research in the field are provided.

COVID-19 Pandemic Effect on Energy Consumption in State Universities: Michoacan, Mexico Case Study

The COVID-19 pandemic has generated multiple impacts. In particular, in the educational sector, the virtual class modality generated changes in the patterns of energy consumption at the institutional level; the identification of this consumption will allow us to reflect on new energy saving and efficient use strategies. In this research, we present a case study of the effects of the COVID-19 pandemic on electricity consumption in 13 state universities in Michoacán, Mexico. Electric energy consumption has been evaluated before and during the presence of the COVID-19 between 2019 and 2020. The comparative analysis estimated the reduction in energy consumption and its economic and environmental impact. The results show a considerable decrease in electricity consumption, generating an average saving of 76.24 MWh/month, which translates into an annual emission reduction from 2019 to 2020 of approximately 497 TnCO2e, and in economic terms of $8,882.25 USD each month. In general, it was identified that consumption patterns in the use of machinery and computer equipment for administrative activities were drastically reduced. If education continues in virtual or hybrid modes, energy consumption schemes will continue to decline and institutions could move towards resilient, affordable, and sustainable models of energy production and consumption.

Empirical Analysis of the Impact of COVID-19 Social Distancing on Residential Electricity Consumption Based on Demographic Characteristics and Load Shape

Since January 2020, the COVID-19 pandemic has been impacting various aspects of people’s daily lives and the economy. The first case of COVID-19 in South Korea was identified on 20 January 2020. The Korean government implemented the first social distancing measures in the first week of March 2020. As a result, energy consumption in the industrial, commercial and educational sectors decreased. On the other hand, residential energy consumption increased as telecommuting work and remote online classes were encouraged. However, the impact of social distancing on residential energy consumption in Korea has not been systematically analyzed. This study attempts to analyze the impact of social distancing implemented as a result of COVID-19 on residential energy consumption with time-varying reproduction numbers of COVID-19. A two-way fixed effect model and demographic characteristics are used to account for the heterogeneity. The changes in household energy consumption by load shape group are also analyzed with the household energy consumption model. There some are key results of COVID-19 impact on household energy consumption. Based on the hourly smart meter data, an average increase of 0.3% in the hourly average energy consumption is caused by a unit increase in the time-varying reproduction number of COVID-19. For each income, mid-income groups show less impact on energy consumption compared to both low-income and high-income groups. In each family member, as the number of family members increases, the change in electricity consumption affected by social distancing tends to decrease. For area groups, large area consumers increase household energy consumption more than other area groups. Lastly, The COVID-19 impact on each load shape is influenced by their energy consumption patterns.