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Viac informácií o knihe Probabilistic Reliability Analysis of Power Systems

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Anotácia knihy

This textbook provides an introduction to probabilistic reliability analysis of power systems. It discusses a range of probabilistic methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic methods for modelling renewable energy sources. The textbook describes real-life studies, discussing practical examples and providing interesting problems, teaching students the methods in a thorough and hands-on way. The textbook has chapters dedicated to reliability models for components (reliability functions, component life cycle, two-state Markov model, stress-strength model), small systems (reliability networks, Markov models, fault/event tree analysis) and large systems (generation adequacy, state enumeration, Monte-Carlo simulation). Moreover, it contains chapters about probabilistic optimal power flow, the reliability of underground cables and cyber-physical power systems. After reading this book, engineering students will be able to apply various methods to model the reliability of power system components, smaller and larger systems. The textbook will be accessible to power engineering students, as well as students from mathematics, computer science, physics, mechanical engineering, policy & management, and will allow them to apply reliability analysis methods to their own areas of expertise.

Parametre knihy

Zaradenie knihy Knihy po nemecky Naturwissenschaften, Medizin, Informatik, Technik Technik Wärme-, Energie- und Kraftwerktechnik

• Celý názov: Probabilistic Reliability Analysis of Power Systems
• Autor: José L. Rueda Torres, Mart A. M. M. van der Meijden, Francisco M. Gonzalez-Longatt, Alexandru I. Stefanov
• Jazyk: Angličtina
• Väzba: Brožovaná
• Počet strán: 348
• EAN: 9783030435004
• ISBN: 3030435008
• ID: 35722110
• Nakladateľ: Springer Nature Switzerland AG
• Hmotnosť: 528 g
• Rozmery: 235 × 155 × 19 mm
• Dátum vydania: 23. April 2021

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