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Fractal Tomography for Power Grids / / by S. D. Varwandkar, M. V. Hariharan



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Autore: Varwandkar S. D Visualizza persona
Titolo: Fractal Tomography for Power Grids / / by S. D. Varwandkar, M. V. Hariharan Visualizza cluster
Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Edizione: 1st ed. 2023.
Descrizione fisica: 1 online resource (100 pages)
Disciplina: 621.319
Soggetto topico: Electric power production
Computational intelligence
Electric power distribution
Electrical Power Engineering
Computational Intelligence
Energy Grids and Networks
Altri autori: HariharanM. V  
Nota di contenuto: Introduction -- Active Network Twins -- Fractals and tomographs -- Editing -- Power Reversals and Loop Flows -- Blackouts -- Frequency Rendezvous -- Blockchain.
Sommario/riassunto: The book introduces a new concept of Fractal Tomograph (FT) to study large and small perturbations of power grids. A mathematical phrase called Active Network Twins (ANT) is discovered which bears astonishing similarity with the human DNA. ANT forms the backbone of analysis. Lineflows and load voltages are compositions of ANT, called fractals which constitute tomographs. First three chapters discuss these new concepts. A remarkable feature is that a minute observation of tomograph is sufficient to detect a malaise in the past, present, or future of the grid. Editing like in genes, to control flows and voltages, is explained in chapter 4. The baffling loop flows in the US-Canada region, a metropolitan blackout in India, and outages in Nepal are illustrated with notional networks. Causes are crisply identified (chapters 5 and 6). Frequency rendezvous and blockchain approach to electricity costs (chapters 7, 8) are radically new perspectives. The book is useful for grid controllers and researchers.
Titolo autorizzato: Fractal Tomography for Power Grids  Visualizza cluster
ISBN: 981-9934-43-5
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910734881503321
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Serie: SpringerBriefs in Computational Intelligence, . 2625-3712