ABSTRACT
This study evaluates the effect of complete nationwide lockdown in 2020 on residential electricity demand across 13 Indian cities and the role of digitalisation using a public smart meter dataset. We undertake a data-driven approach to explore the energy impacts of work-from-home norms across five dwelling typologies. Our methodology includes climate correction, dimensionality reduction and machine learning-based clustering using Gaussian Mixture Models of daily load curves. Results show that during the lockdown, maximum daily peak demand increased by 150-200% as compared to 2018 and 2019 levels for one room-units (RM1), one bedroom-units (BR1) and two bedroom-units (BR2) which are typical for low- and middle-income families. While the upper-middle- and higher-income dwelling units (i.e., three (3BR) and more-than-three bedroom-units (M3BR)) saw night-time demand rise by almost 44% in 2020, as compared to 2018 and 2019 levels. Our results also showed that new peak demand emerged for the lockdown period for RM1, BR1 and BR2 dwelling typologies. We found that the lack of supporting socioeconomic and climatic data can restrict a comprehensive analysis of demand shocks using similar public datasets, which informed policy implications for India's digitalisation. We further emphasised improving the data quality and reliability for effective data-centric policymaking.
ABSTRACT
This study aims to grasp the lifestyle changes in residential buildings related to energy consumption since the emergence of Covid-19 in Indonesia. Data collection through online questionnaires was conducted from more than 1,000 households domiciled in the five largest islands of Indonesia (Sumatra, Java, Kalimantan, Sulawesi, and Papua). Firstly, this article summarizes the results of questionnaire, including the household's basic information and the lifestyle changes. It is found that more than 89% of families have implemented Work from Home (WFH) affecting other lifestyle changes during the pandemic. Secondly, the Multiple Regression Analysis (MRA) was conducted to find influential factors on electricity use in residential housing. It was found that the number of family members, the use of air conditioning, and the use of kitchen appliances significantly contributed to the increase in electricity during stay homes period. Thirdly, the characteristics and lifestyle attributes are classified, the largest increase occurred in household groups with middle to upper average electricity consumption before the pandemic. Finally, the discussion results are expected to encourage industry and policymakers to implement energy monitors, especially regarding electricity use in residential homes. In addition, periodic surveys of post-occupancy evaluations (POE) in households need to be implemented to obtain detailed data in monitoring people's lifestyle and energy use behavior. This study can also be used as a report on energy performance in the residential sector to increase awareness of energy savings and encourage the government to develop renewable energy distribution. Especially to avoid an energy crisis due to disasters that force residents to stay at home during a pandemic.
ABSTRACT
OBJECTIVE: To investigate the impact of coronavirus disease 2019 (COVID-19) on psychosocial and behavioral responses of the non-health care workforce and to evaluate transmission prevention behavior implementation in the workplace. PARTICIPANTS AND METHODS: We deployed the baseline questionnaire of a prospective online survey from November 20, 2020, through February 8, 2021 to US-based employees. The survey included questions on psychosocial and behavioral responses in addition to transmission prevention behaviors (e.g., mask wearing). Select questions asked employees to report perceptions and behaviors before and during the COVID-19 pandemic. Data were analyzed descriptively and stratified by work from home (WFH) percentage. RESULTS: In total, 3607 employees from 8 companies completed the survey. Most participants (70.0%) averaged 90% or more of their time WFH during the pandemic. Employees reported increases in stress (54.0%), anxiety (57.4%), fatigue (51.6%), feeling unsafe (50.4%), lack of companionship (60.5%), and feeling isolated from others (69.3%) from before to during the pandemic. Productivity was perceived to decrease for 42.9% of employees and non-work-related screen time and alcohol consumption to increase for 50.7% and 25.1% of employees, respectively, from before to during the pandemic. Adverse changes were worse among those with lower WFH percentages. Most employees reported wearing a mask (98.2%), washing hands regularly (95.7%), and physically distancing (93.6%) in the workplace. CONCLUSION: These results suggest worsened psychosocial and behavioral outcomes from before to during the COVID-19 pandemic and higher transmission prevention behavior implementation among non-health care employees. These observations provide novel insight into how the COVID-19 pandemic has impacted non-health care employees.