Predicting the output of a PV plant: Application of artificial neural networks - Softcover

Cissé, Abdou Aziz; Diallo, Mamadou Salif

Softcover

ISBN 10: 6203354201 ISBN 13: 9786203354201

Verlag: Our Knowledge Publishing, 2021

Inhaltsangabe

Energy market players (investors, power producers, grid operators, consumers, etc.) are facing potential challenges such as the growing demand for energy, new patterns of energy consumption, the integration of (intermittent) renewable energy sources into power grids and the evolution of power grids.This book investigates the possibility of predicting the production of a self-consuming photovoltaic installation by artificial neural networks. We cross-compared two neural network architectures (looped and unlooped) with respect to multivariate regression in order to have an efficient and reliable tool for predicting the production of a PV installation based on meteorological data (sunshine and ambient temperature).To do so, we used monitoring data of a plant over a 72-day period to build, train and test two neural network topologies (looped and unlooped) which are trained with the Levenberg-Marquardt algorithm.

Über diesen Titel

Über die Autorin bzw. den Autor

Research engineer specialising in renewable energies and intelligent systems. Graduated with a Bachelor's degree in Applied Solar Technology from the University of Ouagadougou (Burkina Faso) and a Research Master's degree from the Ecole Polytechnique de Thiès (Senegal). Research areas: Renewable Energy - Intelligent Systems - AI & Machine Learning.

Details zur Ausgabe

• Verlag: Our Knowledge Publishing
• Erscheinungsdatum: 2021
• Sprache: Englisch
• ISBN 10: 6203354201
• ISBN 13: 9786203354201
• Einband: Taschenbuch
• Anzahl der Seiten: 64
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: preigu; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; 49078; Deutschland