eBook - PDF
Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis
- 360 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis
About this book
Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis addresses uncertainty issues in photovoltaic power generation while also supporting the collaborative enhancement of understanding and applying theory and methods through the integration of models, cases, and code. The book employs StaRAI to address uncertainty analysis and modeling issues at different time scales in photovoltaic power generation, including photovoltaic power prediction, probabilistic power flow, stochastic planning, and more. Chapters cover uncertainty of PV power generation from short to long time scales, including day-ahead scheduling (24 hours in advance), intraday scheduling (minute to hour rolling), and grid planning (15 years).Other sections study the impact of photovoltaic uncertainty on the power grid, offering the most classic cases of probabilistic load flow and PV stochastic planning.The theoretical content of this book is not only systematic but supplemented with concrete examples and MATLAB/Python codes. Its contents will be of interest to all those working on photovoltaic planning, power generation, power plants, and applications of AI, including researchers, advanced students, faculty engineers, R&D, and designers.
- Explores how Statistical Relational Artificial Intelligence (StaRAI) can be applied to photovoltaic power prediction, maintenance, and planning
- Provides a theoretical framework supported by schematic diagrams, real examples, and code
- Discusses the potential for groundbreaking AI applications in PV, future opportunities, and ethical and societal impacts
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis by Xueqian Fu in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Energy. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Front Cover
- Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis
- Statistical Relational Artificial Intelligence in Photovoltaic Power Uncertainty Analysis
- Copyright
- Contents
- Contributors
- About the author
- Preface
- Acknowledgments
- 1 - Review on PV uncertainty model
- 2 - LSTM-based day-ahead photovoltaic power prediction
- 3 - Transformer-based intraday photovoltaic power prediction
- 4 - Unsupervised learning-based annual photovoltaic power scenarios reduction
- 5 - Generative adversarial networkābased annual photovoltaic power simulation
- 6 - Photovoltaic power generation meteorological information mining and forecasting
- 7 - Statistical machine learningābased probabilistic power flow in PV-integrated grid
- 8 - Statistical machine learningābased stochastic planning for photovoltaics
- 9 - Future predictions and summary
- Index
- Back Cover