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Solar Irradiance and Photovoltaic Power Forecasting.

Solar Irradiance and Photovoltaic Power Forecasting.

・ISBN 978-1-032-06814-5 paper GB£ 55.99

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お気に入り
電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 9781003203971
著者・編者Yang, Dazhi / Kleissl, Jan,
シリーズ (Energy Analytics)
出版社 (CRC Press, UK)
出版年月2025
ページ数659 pp.
言語ENG
ニュース番号<A04-82826>

解説

Forecasting plays an indispensable role in grid integration of solar energy, which is an important pathway toward the grand goal of achieving planetary carbon neutrality. This rather specialized field of solar forecasting constitutes both irradiance and photovoltaic power forecasting. Its dependence on atmospheric sciences and implications for power system operations and planning make the multi-disciplinary nature of solar forecasting immediately obvious. Advances in solar forecasting represent a quiet revolution, as the landscape of solar forecasting research and practice has dramatically advanced as compared to just a decade ago.

Solar Irradiance and Photovoltaic Power Forecasting provides the reader with a holistic view of all major aspects of solar forecasting: the philosophy, statistical preliminaries, data and software, base forecasting methods, post-processing techniques, forecast verification tools, irradiance-to-power conversion sequences, and the hierarchical and firm forecasting framework. The book's scope and subject matter are designed to help anyone entering the field or wishing to stay current in understanding solar forecasting theory and applications. The text provides concrete and honest advice, methodological details and algorithms, and broader perspectives for solar forecasting.

Both authors are internationally recognized experts in the field, with notable accomplishments in both academia and industry. Each author has many years of experience serving as editors of top journals in solar energy meteorology. The authors, as forecasters, are concerned not merely with delivering the technical specifics through this book, but more so with the hopes of steering future solar forecasting research in a direction that can truly expand the boundary of forecasting science.