Forecast and Energy Management of a Microgrid with Renewable Energy Sources Using Artificial Intelligence
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,...
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Published in | Intelligent Computing Systems Vol. 820; pp. 81 - 96 |
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Main Authors | , , , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2018
Springer International Publishing |
Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get full text |
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Summary: | 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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ISBN: | 9783319762609 3319762605 |
ISSN: | 1865-0929 1865-0937 |
DOI: | 10.1007/978-3-319-76261-6_7 |