Statistical Relational AI for PV Multi-Timescale Uncertainty Modeling : Theory, Case Analysis, and Engineering Practice

Lingua: inglese

Editore: John Wiley & Sons Inc Jan 2027, 2027

1394439113 / 9781394439119

Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

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EUR 188,91

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Spedito da Germania a U.S.A.

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Descrizione dell’articolo da parte del venditore

Neuware - A unified framework for photovoltaic multi-timescale uncertainty modeling Research on photovoltaic uncertainty remains fragmented: physical models lack interpretability, deep learning sacrifices generalizability, and no end-to-end solutions exist for real grid scenarios. Statistical Relational AI for PV Multi-Timescale Uncertainty Modeling: Theory, Case Analysis, and Engineering Practice delivers a unified framework integrating real-world PV power data with complete workflows for grid planning, operation, and uncertainty-aware decision-making. The book systematically addresses how weather conditions, seasonal patterns, and time-of-day effects drive generation variability across multiple time scales. Case studies drawn from operational PV plants and real power system environments demonstrate a complete workflow from problem formulation through solution development. Practical datasets, executable code, and engineering examples show how proposed approaches translate into implementable solutions. Readers will also find: - Concrete implementation guidance for statistical relational AI methods applied to data organization, pattern discovery, and supporting analytical tasks- Probabilistic techniques for quantifying PV output variability for stochastic optimization and electricity market operations- A complete end-to-end technical pipeline spanning data acquisition, preprocessing, modeling, forecasting, and engineering deployment- A structured perspective on future development trajectories for AI-driven photovoltaic uncertainty research and applications- Solutions designed specifically for real PV grid scenarios rather than idealized or purely simulated environments Designed for university faculty, academic researchers, power-system engineers, and graduate students, this book provides structured methodologies and reproducible tools for modeling PV uncertainty across time scales. Grid planners and renewable energy technology practitioners will also find directly applicable workflows for operational decision-making.…

Codice articolo 9781394439119

Titolo
Statistical Relational AI for PV Multi-Timescale Uncertainty Modeling : Theory, Case Analysis, and Engineering Practice
Autore
Xueqian Fu
Editore
John Wiley & Sons Inc Jan 2027
Anno di pubblicazione
2027
Condizione
Neu
Rilegatura
Buch
Lingua
inglese
ISBN 10
1394439113
ISBN 13
9781394439119
Peso dell'articolo
666 grammi

AHA-BUCH GmbH

Einbeck, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 14 agosto 2006

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 7 a 10 giorni lavorativiDa 5 a 7 giorni lavorativi
Primo articoloEUR 35,00EUR 45,00
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