A viability study of renewables and energy storage systems using multicriteria decision making and an evolutionary approach

Carolina G. Marcelino*, Carlos E. Pedreira, Manuel Baumann, Marcel Weil, Paulo E.M. Almeida, Elizabeth F. Wanner

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationEvolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings
EditorsKaisa Miettinen, Sanaz Mostaghim, Kathrin Klamroth, Carlos A. Coello Coello, Patrick Reed, Kalyanmoy Deb, Erik Goodman
PublisherSpringer
Pages655-668
Number of pages14
ISBN (Print)9783030125974
DOIs
Publication statusPublished - 3 Feb 2019
Event10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019 - East Lansing, United States
Duration: 10 Mar 201913 Mar 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11411 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019
CountryUnited States
CityEast Lansing
Period10/03/1913/03/19

Fingerprint

Energy Storage
Multicriteria Decision-making
Storage System
Microgrid
Viability
Energy storage
Decision making
Battery
Environmental impact
Life Cycle Assessment
Lithium-ion Battery
Grid
Electric power generation
Power Distribution
Renewable Energy
Distribution System
Costs
Swarm
Energy
Electricity

Keywords

  • Evolutionary swarm
  • Life Cycle Assessment
  • Multicriteria decision making
  • Optimization
  • Renewable energy
  • Smart grids

Cite this

Marcelino, C. G., Pedreira, C. E., Baumann, M., Weil, M., Almeida, P. E. M., & Wanner, E. F. (2019). A viability study of renewables and energy storage systems using multicriteria decision making and an evolutionary approach. In K. Miettinen, S. Mostaghim, K. Klamroth, C. A. Coello Coello, P. Reed, K. Deb, & E. Goodman (Eds.), Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings (pp. 655-668). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11411 LNCS). Springer. https://doi.org/10.1007/978-3-030-12598-1_52
Marcelino, Carolina G. ; Pedreira, Carlos E. ; Baumann, Manuel ; Weil, Marcel ; Almeida, Paulo E.M. ; Wanner, Elizabeth F. / A viability study of renewables and energy storage systems using multicriteria decision making and an evolutionary approach. Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. editor / Kaisa Miettinen ; Sanaz Mostaghim ; Kathrin Klamroth ; Carlos A. Coello Coello ; Patrick Reed ; Kalyanmoy Deb ; Erik Goodman. Springer, 2019. pp. 655-668 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Marcelino, CG, Pedreira, CE, Baumann, M, Weil, M, Almeida, PEM & Wanner, EF 2019, A viability study of renewables and energy storage systems using multicriteria decision making and an evolutionary approach. in K Miettinen, S Mostaghim, K Klamroth, CA Coello Coello, P Reed, K Deb & E Goodman (eds), Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11411 LNCS, Springer, pp. 655-668, 10th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2019, East Lansing, United States, 10/03/19. https://doi.org/10.1007/978-3-030-12598-1_52

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; Weil, Marcel; Almeida, Paulo E.M.; Wanner, Elizabeth F.

Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. ed. / Kaisa Miettinen; Sanaz Mostaghim; Kathrin Klamroth; Carlos A. Coello Coello; Patrick Reed; Kalyanmoy Deb; Erik Goodman. Springer, 2019. p. 655-668 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11411 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Marcelino, Carolina G.

AU - Pedreira, Carlos E.

AU - Baumann, Manuel

AU - Weil, Marcel

AU - Almeida, Paulo E.M.

AU - Wanner, Elizabeth F.

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AB - 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.

KW - Evolutionary swarm

KW - Life Cycle Assessment

KW - Multicriteria decision making

KW - Optimization

KW - Renewable energy

KW - Smart grids

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Marcelino CG, Pedreira CE, Baumann M, Weil M, Almeida PEM, Wanner EF. A viability study of renewables and energy storage systems using multicriteria decision making and an evolutionary approach. In Miettinen K, Mostaghim S, Klamroth K, Coello Coello CA, Reed P, Deb K, Goodman E, editors, Evolutionary Multi-Criterion Optimization - 10th International Conference, EMO 2019, Proceedings. Springer. 2019. p. 655-668. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-12598-1_52