AI-Based Forecasting of Solar Photovoltaics Power Generation.

Format:

Book

Author/Creator:

Shirazi, Elham.

Contributor:

van Sark, Wilfried.

Series:

Energy Engineering Series

Language:

English

Physical Description:

1 online resource (308 pages)

Edition:

1st ed.

Place of Publication:

Stevenage : Institution of Engineering & Technology, 2026.

Summary:

This book conveys approaches for using AI for improved PV forecasting, which is imperative in increasing the share of clean power to achieve decarbonisation of the energy system. Chapters cover machine and deep learning, evaluation, grid integration and case studies.

Contents:

Intro

Contents

Preface

About the editors

1. Introduction to solar photovoltaics forecasting | Elham Shirazi and Wilfried van Sark

2. Data, data collection, and preprocessing for solar photovoltaics forecasting | Lennard Visser and Wilfried van Sark

3. Statistical time series for solar photovoltaic forecasting | Ioannis K. Bazionis, Athina P. Georgilaki and Pavlos S. Georgilakis

4. Machine learning approaches for PV forecasting | Markos A. Kousounadis-Knousen, Athina P. Georgilaki and Pavlos S. Georgilakis

5. Deep learning approaches for PV forecasting | Emanuele Ogliari, Maciej Sakwa, Silvana Matrone and Sonia Leva

6. Hybrid and ensemble models for solar energy forecast | Emanuele Ogliari, Silvana Matrone, Binh Nam Nguyen and Sonia Leva

7. Probabilistic PV forecasting | Martin János Mayer and Sándor Baran

8. Model optimisation, hyperparameter tuning and performance evaluation in machine learning models for solar PV generation forecast | Hugo Quest, Christophe Ballif and Elham Shirazi

9. Sky imager based solar photovoltaic forecast | Khadija Barhmi, Elham Shirazi, Sara Mirbagheri Golroodbari and Wilfried van Sark

10. Solar photovoltaic forecasting for energy system integration and control | Silvana Matrone, Amirhossein Heydarian Ardakani, Emanuele Ogliari, Sonia Leva and Elham Shirazi

Index.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-80705-010-6

1-83724-020-5

9781807050108

OCLC:

1584474107