A Viability Study of Renewables and Energy Storage Systems Using Multicriteria Decision Making and an Evolutionary Approach
Renewable energy technologies use natural sources, such as wind and solar, to produce electricity. Nowadays, there is a global sustainable electric power generation pressure to alleviate environmental impacts caused by the usage of fossil fuels. Energy market is focused on improving those technologi...
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Published in | Evolutionary Multi-Criterion Optimization pp. 655 - 668 |
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Main Authors | , , , , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
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Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | Renewable energy technologies use natural sources, such as wind and solar, to produce electricity. Nowadays, there is a global sustainable electric power generation pressure to alleviate environmental impacts caused by the usage of fossil fuels. Energy market is focused on improving those technologies by meeting customer needs, but it proves to be challenging. Renewable power production integrated with a Hybrid Micro-Grid System (HMGS), a power distribution system composed of one or more distributed sources, may provide a reliable and cost-effective solution. This paper proposes a grid-connected HMGS model able of planning energy production and operating in parallel autonomously or connected on a public grid. The optimization of such HMGS is done using a swarm evolutionary approach and the results are obtained using different battery technologies. A life cycle assessment model and a multi-criteria decision making approach are carried out to perform a viability study of the battery technologies. Wind and solar meteorological data from four regions in the Minas Gerais state, Brazil, were used as input for the model. Results show that lithium ion batteries are the most recommendable ones, ensuring not only the minimal cost and losses in the system but also minimizing the environmental impact. |
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ISBN: | 9783030125974 3030125971 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-030-12598-1_52 |