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A Measurement-Driven Digital-Twin Methodology for Flexible Loads Voltage Control in Unknown Grids
No full textVoltage control in modern power systems has become increasingly complex due to the high penetration of renewable generation. Numerous solutions have been proposed from both the transmission and distribution sides, involving generators and system operators. However, the contribution of loads has remained limited, mainly to demand shifting and basic demand response strategies. This work introduces a novel approach that leverages digital twins to enhance the active participation of loads in supporting voltage control. Unlike traditional methods, the proposed framework builds digital twins exclusively from measurable data, enabling virtually any converter-interfaced load connected to a grid, regardless of whether the network is fully known or not, to contribute effectively to voltage regulation. The methodology is first demonstrated through a parametric study, which evaluates the impact of different load behaviors and control strategies on network voltage stability. To further validate the approach, hardware-in-the-loop (HIL) experiments are conducted, confirming the feasibility of real-time implementation. Four voltage control use-cases are developed and tested for a controllable thermal load, showing that even individual loads can provide meaningful support to grid voltage regulation. The results highlight the potential of data-driven digital twins to unlock new, scalable, and flexible contributions from loads, reinforcing the stability of future power systems with high renewable penetration
Diamond Thinking: Infrastruktur trifft Wissenschaftskultur - Diamond_Thinking; Teilvorhaben B am KIT
No full textDiese Veröffentlichung ist der Abschlussbericht für Teilvorhaben B des gemeinsamen, vom BMFTR geförderten Projekts „Diamond Thinking“. Der Bericht stellt die ursprünglichen Ziele, den Ablauf sowie die Ergebnisse von Teilvorhaben B dar, für das das Karlsruher Institut für Technologie (KIT) verantwortlich war. Dieses Teilvorhaben konzentrierte sich auf den Aufbau eines nachhaltigen Publikationsservices für Diamond-Open-Access-Zeitschriften für Mitglieder des KIT
From Matrix to Metrics: Introducing and Applying a Configuration Matrix to Evaluate DMARC Policies
No full textEmail spoofing, the practice of sending illegitimate messages that appear to come from a legitimate sender, is a phishing technique frequently employed by attackers. In an effort to prevent such phishing, anti-spoofing mechanisms like DMARC were introduced and have been examined in the research community with respect to describing adoption rates, policies used, and potential problems. However, prior research has not yet taken into account all aspects of DMARC when evaluating how effectively configurations prevent spoofing attacks. To address this research gap, we developed a utility-oriented configuration matrix – focusing on the anti-spoofing effectiveness of different DMARC configurations – and provide clear recommendations for selecting the appropriate configuration. We then collected data from the Tranco Top-100k list daily for a duration of eight months and applied our classification to the collected data. Our analyses of the collected data reveals how configurations evolve over time and provides insights into the actual deployment of DMARC in practice. This allows us to identify potential issues that hinder the adoption of more secure configurations and to identify the most common errors in invalid DMARC records found in the wild, which could serve as a basis for enhancing the DMARC standard. Our results show that domains move towards configurations that are more effective against email spoofing, however, still exhibiting a lack of knowledge with respect to different policy settings
Supercritical water gasification of lignocellulosic biomass: Kinetic modeling enhanced by Bayesian optimization
No full textA new kinetic model for the supercritical water gasification of lignocellulosic biomass is presented. This model accurately simulates the production of gases up to C products, and distinguishes condensable products as either aqueous condensate or tars. The reaction orders were treated as hyperparameters, which were tuned via Bayesian optimization. The model was validated against experiments conducted in a continuous laboratory plant operating within a broad range of conditions, including variations in temperature (823–973 K), pressure (240–300 bar), biomass content (1.3–6.6 wt%), KCO addition (0–3750 ppm), and residence time (6–48 s). The proposed model provides insight into the behavior of the reactive system and is useful for applications such as scale-up, process optimization, and process design
A novel Multi-Timescale strategy for Fusion Systems Codes and its impact to Fusion Power Plants parametric analyses
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Drastic field-induced resistivity upturns as signatures of unconventional magnetism in superconducting iron chalcogenides
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Searching for Ultra-High Energy Photons applying Convolutional Neural Networks Using the Surface Detector of the Pierre Auger Observatory
No full textIdentifying sources of cosmic rays is challenging, as the charged particles are deflected by magnetic fields and do not point back to their sources. Neutral particles, such as ultra-high energy (UHE) γs will point directly to their sources, unless they interact in the interstellar medium or are absorbed. Cosmic ray detectors such as the 3000 km2 surface array of the Pierre Auger Observatory are capable of observing UHE γs above 1018 eV. With increasing energy, their mean free path allows probing extragalactic sources up to a few Mpc. Different methods like BDTs and air-shower universality have been previously applied to the search of γs at different energy ranges. Although no UHE γs have been found, the obtained bounds of the fluxes provide crucial constraints on cosmic-ray acceleration models. Neural networks have the potential to improve discrimination, enhancing the sensitivity to even lower fluxes. In this work, we present a convolutional neural network designed to distinguish between simulated UHE photon and proton showers. We evaluate possible systematics due to the imperfect simulation of air showers and detector effects using an independent test set and a burn sample consisting of 2% of the available data. Steps for a future unblinding of the search sample are discussed
Stärkenorientierung
No full textDas Video ist Teil des "Digitalen Kulturschule-KITs", welches ein Angebot für Schulleitungen und Schulentwicklungsinteressierte ist, die sich systematisch mit dem Thema Kulturschule auseinandersetzen möchten