Has COVID-19 lockdown impacted on aged care energy use and demand?

Aged Care Energy Use and Peak Demand Change in the COVID-19 Year: Empirical Evidence from Australia

“…These facilities may comprise a mix of resident rooms, resident shared spaces (e.g., dining rooms, activity areas, library), commercial service spaces (e.g., kitchen, laundry, building management), clinical spaces (for nursing, allied health and medical staff and consultants) and retail spaces (e.g., café, hairdresser). A previous study identified that some changes to energy use were observed during a short (6-week) COVID-19 lockdown in early 2020, but that the extent of these changes had a strong relationship with climate [10]. This paper builds on that previous work by evaluating how energy use and peak demand changed for aged care facilities in a COVID-19 year.…”

“…Peak demand is important because of its impact on electrical network, for example high power and high current flow may violate the thermal limits of cables and transformers. Temperature statistics (e.g., cooling degree days (CDD24) in this climatic context) are incorporated into electricity use and peak demand analysis, as energy use can be highly correlated to temperature [10,35]. After obtaining an overall understanding of annual energy use and peak demand in these communities, the next step is to analyze typical demand profiles.…”

“…There are examples or recommended base values from standards or government bodies [45,[47][48][49]. Another issue is that the KPI may not be reliable or robust for sites in temperate climate zones or mild seasons [10]. Because CDD (or HDD) values can be small for RACs in temperate climate zones or in mild seasons, a minor change in energy use for RACs in temperate climate zones or mild seasons may lead to significant increase or decrease for the KPI.…”

“…For example, electricity for space cooling and heating tends to account for the highest energy use in Australian RACs [6][7][8]. Nonetheless, the COVID-19 pandemic has disrupted the way aged care communities operate, promoted vulnerability and resilience considerations [9] and also resulted in changes in energy use and peak demand [10].…”

“…In terms of analyzing energy use and peak demand data, statistical tools and data analytical algorithms can be used. Visualization, such as boxplots or scatterplots, can be very intuitive to present summary statistics or show a relationship [10,21]. Another way to examine change of energy use pattern is by studying how typical demand profiles look like [22].…”