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A Viability Study of Renewables and Energy Storage Systems Using Multicriteria Decision Making and an Evolutionary Approach

Marcelino, Carolina G.; Pedreira, Carlos E.; Baumann, Manuel 1; Weil, Marcel 1; Almeida, Paulo E. M.; Wanner, Elizabeth F.
1 Institut für Technikfolgenabschätzung und Systemanalyse (ITAS), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

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.

DOI: 10.1007/978-3-030-12598-1_52
Zitationen: 6
Zitationen: 6
Zugehörige Institution(en) am KIT Institut für Technikfolgenabschätzung und Systemanalyse (ITAS)
Publikationstyp Buchaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISBN: 978-3-030-12598-1
ISSN: 0302-9743, 1611-3349
KITopen-ID: 1000093551
HGF-Programm 48.01.01 (POF III, LK 01) Innovation Processes+impacts of Technol.
Erschienen in Evolutionary Multi-Criterion Optimization : 10th International Conference (EMO 2019), East Lansing, MI, March 10-13, 2019, Proceedings. Ed.: K. Deb
Verlag Springer International Publishing
Seiten 655–668
Serie Lecture notes in computer science ; 11411
Vorab online veröffentlicht am 03.02.2019
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