Electricity consumption of Singaporean households reveals proactive community response to COVID-19 progression.

Understanding how populations' daily behaviors change during the COVID-19 pandemic is critical to evaluating and adapting public health interventions. Here, we use residential electricity-consumption data to unravel behavioral changes within peoples' homes in this period. Based on smart energy-meter data from 10,246 households in Singapore, we find strong positive correlations between the progression of the pandemic in the city-state and the residential electricity consumption. In particular, we find that the daily new COVID-19 cases constitute the most dominant influencing factor on the electricity demand in the early stages of the pandemic, before a lockdown. However, this influence wanes once the lockdown is implemented, signifying that residents have settled into their new lifestyles under lockdown. These observations point to a proactive response from Singaporean residents-who increasingly stayed in or performed more activities at home during the evenings, despite there being no government mandates-a finding that surprisingly extends across all demographics. Overall, our study enables policymakers to close the loop by utilizing residential electricity usage as a measure of community response during unprecedented and disruptive events, such as a pandemic.

Sleeping behaviors are determined by lockdown and not work-from-home arrangements.

Lockdowns and work-from-home arrangements became abrupt realities for people at an unprecedented scale during the COVID-19 pandemic. Here, considering the case of Singapore, we study how peoples' sleep behaviors-which are closely linked to their mental health-varied as a result. However, different from most studies, this paper uses household electricity consumption data to estimate the sleeping behaviors of nearly 10,000 households in the city-state. With this, we study how the residents' daily sleep durations changed dynamically during the lockdown and afterwards when restrictions were progressively eased, and show their strong connection to major changes in the public health policy and current events during this period. Our results add to the evidence for the stress endured by the populace during the lockdown; we find that sleep durations for all demographics, while higher than before the lockdown, became more fluctuating across days. A major, and surprising, finding is that it was the lockdown that determined the residents' sleeping duration, rather than simply working-from-home arrangements. That is, the sleeping durations largely reverted back to their pre-pandemic levels when the lockdown was lifted-with small variations based on demographic factors-although a vast majority of people continued to work from home. This highlights the resilience of the daily routines of the Singapore populace. While providing insights into how a pandemic influences the dynamics of urban sleep patterns, our finding also has broader implications regarding the efficiency of the workforce, suggesting that concerns about asynchronous work routines and productivity may be overblown.

Coupled power generators require stability buffers in addition to inertia.

Increasing the inertia is widely considered to be the solution to resolving unstable interactions between coupled oscillators. In power grids, Virtual Synchronous Generators (VSGs) are proposed to compensate for reducing inertia as rotating fossil-fuel-based generators are being phased out. Yet, modeling how VSGs and rotating generators simultaneously contribute energy and inertia, we surprisingly find that instabilities of a small-signal nature could arise despite fairly high system inertia if the generators' controls are not coordinated at the system level. Importantly, we show there exist both an optimal and a maximum number of such VSGs that can be safely supported, a previously unknown result directly useful for power utilities in long-term planning and prosumer contracting. Meanwhile, to resolve instabilities in the short term until system-level coordination can be achieved, we argue that the new market should include another commodity that we call stability storage, whereby-analogous to energy storage buffering energy imbalances-VSGs act as decentralized stability buffers. While demonstrating the effectiveness of this concept for a wide range of energy futures, we provide policymakers and utilities with a roadmap towards achieving a 100% renewable grid.

Resilience of urban public electric vehicle charging infrastructure to flooding.

An adequate charging infrastructure is key to enabling high personal electric vehicle (EV) adoption rates. However, urban flooding-whose frequency and intensity are increasing due to climate change-may be an impediment. Here, we study how geographically-correlated outages due to floods impact public EV charging networks in Greater London. While we find no appreciable impact on the ability of battery EVs to serve typical urban driving behaviors, we observe disproportionate stresses on chargers both near, and surprisingly significantly farther from, the flooded regions. For instance, we find over 50% increase in charger utilization and 260% increase in the distance to the nearest available charger in parts of Greater London over 10 km away. Concerningly, the impact is most concentrated on already-stressed sections of the network, underscoring the infrastructure's vulnerability. Finally, we develop and evaluate four strategies for city planners to enhance the flood resilience of cities' public EV charging networks.

Traffic networks are vulnerable to disinformation attacks.

Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers' decisions to create congestion at a city scale. Specifically, we consider two complementary scenarios, one where drivers are persuaded to move towards a given location, and another where they are persuaded to move away from it. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 km from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation.

How weaponizing disinformation can bring down a city's power grid.

Social media has made it possible to manipulate the masses via disinformation and fake news at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be one of the weakest links when protecting critical infrastructure in general, and the power grid in particular. Here, we consider an attack in which an adversary attempts to manipulate the behavior of energy consumers by sending fake discount notifications encouraging them to shift their consumption into the peak-demand period. Using Greater London as a case study, we show that such disinformation can indeed lead to unwitting consumers synchronizing their energy-usage patterns, and result in blackouts on a city-scale if the grid is heavily loaded. We then conduct surveys to assess the propensity of people to follow-through on such notifications and forward them to their friends. This allows us to model how the disinformation may propagate through social networks, potentially amplifying the attack impact. These findings demonstrate that in an era when disinformation can be weaponized, system vulnerabilities arise not only from the hardware and software of critical infrastructure, but also from the behavior of the consumers.