Microgrids are low-voltage distribution network which comprise of controllable loads and distributed energy resources (DERs) that can be used in an isolated or grid-connected mode. the microgrid energy management syst...
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We propose using a hierarchical retail market structure to alert and dispatch resources to mitigate cyber-physical attacks on a distribution grid. We simulate attacks where a number of generation nodes in a distributi...
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ISBN:
(纸本)9798350369274;9798350369281
We propose using a hierarchical retail market structure to alert and dispatch resources to mitigate cyber-physical attacks on a distribution grid. We simulate attacks where a number of generation nodes in a distribution grid are attacked. We show that the market is able to successfully meet the shortfall between demand and supply by utilizing the flexibility of remaining resources while minimizing any extra power that needs to be imported from the main transmission grid. this includes utilizing upward flexibility or reserves of remaining online generators and some curtailment or shifting of flexible loads, which results in higher costs. Using price signals and market-based coordination, the grid operator can achieve its objectives without direct control over distributed energy resources and is able to accurately compensate prosumers for the grid support they provide.
As contemporary computing infrastructures evolve to include diverse architectures beyond traditional von Neumann models, the limitations of classical graph-based infrastructure and application modelling become apparen...
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ISBN:
(纸本)9798400704451
As contemporary computing infrastructures evolve to include diverse architectures beyond traditional von Neumann models, the limitations of classical graph-based infrastructure and application modelling become apparent, particularly in the context of the computing continuum and its interactions with Internet of things (IoT) applications. Hypergraphs prove instrumental in overcoming this obstacle by enabling the representation of computing resources and data sources irrespective of scale. this allows the identification of new relationships and hidden properties, supporting the creation of a federated, sustainable, cognitive computing continuum with shared intelligence. the paper introduces the HyperContinuum conceptual platform, which provides resource and applications management algorithms for distributed applications in conjunction with next-generation computing continuum infrastructures based on novel von Neumann computer architectures. the HyperContinuum platform outlines high-order hypergraph applications representation, sustainability optimization for von Neumann architectures, automated cognition through federated learning for IoT application execution, and adaptive computing continuum resources provisioning.
the intention present day this paper is to advise a dispensed deep ultra-modern (DL) architecture for 5G network slicing. the proposed allotted DL structure utilizes distributed nodes to learn about the network slices...
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Recent advancements in technology have resulted in the creation of novel approaches for administering organ donation systems, with an objective of overcoming the restrictions of traditional centrally controlled system...
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distributed storage systems offer scalable and cost-effective solutions for managing large data collections. A critical factor for the adoption of these systems is the allocation of data (possibly including replicas) ...
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the 4th Industrial Revolution has driven innovations in integrating Information Technologies (IT) with Operations Technologies (OT). this integration is essential for developing Cyber-Physical Production systems (CPPS...
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In the rapidly advancing realm of virtual banking, a robust data strategy is crucial for competitiveness and meeting growing customer demands. In 2025, the Bank of thailand will be issued three virtual banking license...
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the terminal devices in the energy system face limitations in communication resources, storage space, computational power, and data security, making it challenging to train and deploy computationally intensive artific...
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ISBN:
(纸本)9798350361018;9798350361001
the terminal devices in the energy system face limitations in communication resources, storage space, computational power, and data security, making it challenging to train and deploy computationally intensive artificial intelligence models. therefore, employing communication-efficient federated learning to train lightweight neural network models is a suitable solution. In this paper, we propose decentralized federated learning with efficient communication achieved by cyclically broadcasting weight parameters from each device during the model training process. We explore the proposed decentralized federated learning framework using energy disaggregation as a case study. Furthermore, grouped convolution is introduced to establish lightweight models, reducing the computational and storage costs during boththe training process and model deployment. We conducted extensive experiments on publicly available datasets to validate that the proposed decentralized federated learning approach exhibits significant communication efficiency and minimal impact on the performance of the global model.
Quantum computing is newly emerging information-processing technology which is foreseen to be exponentially faster than classical supercomputers. Current quantum processors are nevertheless very limited in their avail...
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ISBN:
(纸本)9788088365150
Quantum computing is newly emerging information-processing technology which is foreseen to be exponentially faster than classical supercomputers. Current quantum processors are nevertheless very limited in their availability and performance and many important software tools for them do not exist yet. therefore, various systems are studied by simulating the run of quantum computers. Building upon our previous experience with quantum computing of small molecular systems (see I. Mihalikova et al., Molecules 27 (2022) 597, and I. Mihalikova et al., Nanomaterials 2022, 12, 243), we have recently focused on computing electronic structure of periodic crystalline materials. Being inspired by the work of Cerasoli et al. (Phys. Chem. Chem. Phys., 2020, 22, 21816), we have used hybrid variational quantum eigensolver (VQE) algorithm, which combined classical and quantum information processing. Employing tight-binding type of crystal description, we present our results for crystalline diamond-structure silicon. In particular, we focus on the states along the lowest occupied band within the electronic structure of Si and compare the results with values obtained by classical means. While we demonstrate an excellence agreement between classical and quantum-computed results in most of our calculations, we further critically check the sensitivity of our results with respect to computational set-up in our quantum-computing study. A few results were obtained also using quantum processors provided by the IBM.
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