The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the US becoming the epicenter of COVID-19 cases since late March. As the US begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing US wholesale electricity markets with COVID-19 case, weather, mobile device location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we rigorously uncover a significant reduction in electricity consumption that is strongly correlated with the number of COVID-19 cases, degree of social distancing, and level of commercial activity.

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Pure ZnO, ZnO–CuO nanocomposites can be synthesized by using a modified perfume spray pyrolysis method (MSP). The crystallite size of the nanoparticles (NPs) has been observed by X-ray diffraction pattern and is nearly 36 nm. Morphological studies have been analyzed by using Field Emission Scanning Electron Microscopy (FESEM) and its elemental analysis was reported by Elemental X-ray Analysis (EDX); these studies confirmed that ZnO and CuO have hexagonal structure and monoclinic structure respectively. Fourier Transform Infrared (FTIR) spectra revealed that the presence of functional frequencies of ZnO and CuO were observed at 443 and 616 cm−1. The average bandgap value at 3.25 eV using UV–vis spectra for the entitled composite has described a blue shift that has been observed here. The antibacterial study against both gram positive and negative bacteria has been studied by the disc diffusion method. To the best of our knowledge, it is the first report on ZnO–CuO nanocomposite synthesized by a modified perfume spray pyrolysis method.

Abstract-We synthesize performance-aware safe cruise control policies for longitudinal motion of platoons of autonomous vehicles. Using set-invariance theories, we guarantee infinitetime collision avoidance in the presence of bounded additive disturbances, while ensuring that the length and the cruise speed of the platoon are bounded within specified ranges. We propose (i) a centralized control policy, and (ii) a distributed control policy, where each vehicle's control decision depends solely on its relative kinematics with respect to the platoon leader. Numerical examples are included.

We consider the problem of designing distributed controllers to guarantee dissipativity of a networked system comprised of dynamically coupled subsystems. We require that the control synthesis is carried out locally at the subsystem-level, without explicit knowledge of the dynamics of other subsystems in the network. We solve this problem in two steps. First, we provide an approach to decompose a dissipativity condition on the networked dynamical system into equivalent conditions on the dissipativity of individual subsystems. We then use these distributed dissipativity conditions to synthesize controllers locally at the subsystem-level, using only the knowledge of the dynamics of that subsystem, and limited information about the dissipativity of the subsystems to which it is dynamically coupled. We show that the subsystem-level controllers synthesized in this manner are sufficient to guarantee dissipativity of the networked dynamical system. We also provide an approach to make this synthesis compositional, that is, when a new subsystem is added to an existing network, only the dynamics of the new subsystem, and information about the dissipativity of the subsystems in the existing network to which it is coupled are used to design a controller for the new subsystem, while guaranteeing dissipativity of the networked system including the new subsystem. Finally, we demonstrate the application of this synthesis in enabling plugand-play operations of generators in a microgrid by extending our results to networked switched systems.

The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the U.S. becoming the epicenter of COVID-19 cases since late March. As the U.S. begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector.Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing U.S. wholesale electricity markets with COVID-19 case, weather, mobile device location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we rigorously uncover a significant reduction in electricity consumption that is strongly correlated with the number of COVID-19 cases, degree of social distancing, and level of commercial activity.

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