2,071 research outputs found

    From an Autonomous to a Collaborative Website Redesign Process: The University of Denver Libraries Experience

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    Librarians traditionally have insisted on designing and developing the library’s website in-house. An inhouse developed website allows librarians full control of its design, content, and delivery. The library website is also distinguished by its research orientation compared to the university’s marketing-driven purposes. However, in the age of gaining competitive advantage by promoting campus branding, shared services, and collaborative initiatives by various administrative units, libraries could be a stronger partner with other campus departments. This article describes the University of Denver Libraries’ transformation from an autonomous information silo to an integrated Web portal within the University’s Marketing & Communication division. In the course of this change, unlike turning a switch on or off, the librarians experienced stages of uncertainty, denial, negotiation, and acceptance. The project was successfully completed and became an exemplar for many other campus-wide initiatives. By sharing this experience, the authors hope to encourage other libraries to consider the tangible and intangible benefits that university-wide collaborations can elicit

    Online learning for robust voltage control under uncertain grid topology

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    Voltage control generally requires accurate information about the grid's topology in order to guarantee network stability. However, accurate topology identification is challenging for existing methods, especially as the grid is subject to increasingly frequent reconfiguration due to the adoption of renewable energy. Further, running existing control mechanisms with incorrect network information may lead to unstable control. In this work, we combine a nested convex body chasing algorithm with a robust predictive controller to achieve provably finite-time convergence to safe voltage limits in the online setting where the network topology is initially unknown. Specifically, the online controller does not know the true network topology and line parameters, but instead learns them over time by narrowing down the set of network topologies and line parameters that are consistent with its observations and adjusting reactive power generation accordingly to keep voltages within desired safety limits. We demonstrate the effectiveness of our approach in a case study on a Southern California Edison 56-bus distribution system. Our experiments show that in practical settings, the controller is indeed able to narrow the set of consistent topologies quickly enough to make control decisions that ensure stability in both linearized and realistic non-linear models of the distribution grid.Comment: under submission. arXiv admin note: substantial text overlap with arXiv:2206.1436
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