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Carry Value Transformation (CVT) is a model of discrete dynamical system which is one special case of Integral Value Transformations (IVTs). Earlier in [5] it has been proved that sum of two non-negative integers is equal to the sum of…
With the rapid growth of power market reform and power demand, the power transmission capacity of a power grid is approaching its limit, and the secure and stable operation of power systems becomes increasingly important. In particular, in…
This work presents (i) a framework for certifying small-signal frequency stability of a power system with line dynamics and heterogeneous bus dynamics, (ii) a novel reduced-order model of damper windings in synchronous machines, and (iii) a…
The future electric grid will consist of significant penetration of renewable and distributed generation that is likely to create a homogenous transmission and distribution (T&D) system, requiring tools that can model and robustly simulate…
Non-Gaussian operations on two mode squeezed vacuum states (TMSV) in continuous variable measurement device independent quantum key distribution (CV-MDI-QKD) protocols have been shown to effectively increase the total transmission distances…
Grid-forming voltage source converters (GFM-VSCs) are emerging as a solution for integrating renewable energy resources (RERs) into power systems. GFM-VSCs need a self-synchronisation strategy to ensure that all converters and generators in…
In this paper, a design space exploration of power delivery networks is performed for multi-chip 2.5-D and 3-D IC technologies. The focus of the paper is the effective placement of the voltage regulator modules (VRMs) for power supply noise…
VSG control has emerged as a crucial technology for integrating renewable energy sources. However, renewable energy have limited tolerance to overcurrent, necessitating the implementation of current limiting (CL)strategies to mitigate the…
High-voltage direct current (HVDC) transmission applications and the growth of the dynamic load in large-scale receiving-end grids lead to a higher risk of short-term voltage instability. An effective way to address this problem is to…
Connected vehicles (CVs) can capture and transmit detailed data such as vehicle position and speed through vehicle-to-vehicle and vehicle-to-infrastructure communications. The wealth of CV data provides new opportunities to improve safety…
Distribution networks face challenges from the increasing deployment of Distributed Energy Resources (DERs) and the emergence of bidirectional power flows. We propose a decentralized Volt/VAr control method based on a saddle-point…
For active distribution networks (ADNs) integrated with massive inverter-based energy resources, it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs. Thus, current models of…
Understanding motorist detouring behavior is critical for both traffic operations and planning applications. However, measuring real-world detouring behavior is challenging due to the need to track the movement of individual vehicles.…
With the rising demand for solar energy installation, there is a pressing need for utilities to regulate the voltages at the distribution level. In grids with high penetration of photovoltaic (PV) systems, voltage fluctuations can occur at…
Distributed energy resources (DERs) installed at electric distribution networks create different opportunities and challenges for the distribution system operator (DSO). By increasing the penetration level of DERs, the impacts of these…
Due to generation retirements and growth of renewable energy sources integration, there will be widespread changes in the real and reactive power flow in nowadays power systems. These changes also bring about challenges on system operation…
LLMs are widely adopted in production, pushing inference systems to their limits. Disaggregated LLM serving (e.g., PD separation and KV state disaggregation) improves scalability and cost efficiency, but it also turns KV into an explicit…
Compressed sensing (CS) is a sampling paradigm that allows to simultaneously measure and compress signals that are sparse or compressible in some domain. The choice of a sensing matrix that carries out the measurement has a defining impact…
Channel estimation at the receiver side is essential to adaptive modulation schemes, prohibiting low complexity systems from using variable rate and/or variable power transmissions. Towards providing a solution to this problem, we introduce…
This paper presents ConVex optimization-based Stochastic steady-state Tracking Error Minimization (CV-STEM), a new state feedback control framework for a class of Ito stochastic nonlinear systems and Lagrangian systems. Its innovation lies…