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2018 | OriginalPaper | Buchkapitel

Forecast and Energy Management of a Microgrid with Renewable Energy Sources Using Artificial Intelligence

verfasst von : E. Cruz May, L. J. Ricalde, E. J. R. Atoche, A. Bassam, E. N. Sanchez

Erschienen in: Intelligent Computing Systems

Verlag: Springer International Publishing

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Abstract

This paper presents a design of an artificial neural network algorithm for prediction and management of electric loads for the optimal operation of a microgrid with sources of renewable energy. The hybrid power generation system is composed of a photovoltaic array, wind turbines, public power grid, electric loads and battery bank as a storage system. A dynamic neural network is implemented to determine the optimal amounts of energy that must be obtained from the sources, to reduce costs and improve efficiency. Simulation results demonstrate that generation of each energy source can be reached in an optimal form using the proposed design.

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Titel: Forecast and Energy Management of a Microgrid with Renewable Energy Sources Using Artificial Intelligence
verfasst von: E. Cruz May
L. J. Ricalde
E. J. R. Atoche
A. Bassam
E. N. Sanchez
Verlag: Springer International Publishing
Buch: Intelligent Computing Systems
Print ISBN: 978-3-319-76260-9

Electronic ISBN: 978-3-319-76261-6

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-76261-6_7

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