Detalhes bibliográficos
| Ano de defesa: |
2021 |
| Autor(a) principal: |
MARTINS JÚNIOR, Clóvis Da Conceição Melo |
| Orientador(a): |
CASAS, Vicente Leonardo Paucar |
| Banca de defesa: |
CASAS, Vicente Leonardo Paucar,
COSTA FILHO, Raimundo Nonato Diniz,
BRANCO, Tadeu da Mata Medeiros,
OLIVEIRA, Denisson Queiroz |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal do Maranhão
|
| Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUACAO EM EDUCAÇÃO FÍSICA
|
| Departamento: |
DEPARTAMENTO DE EDUCAÇÃO FÍSICA/CCBS
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
https://tedebc.ufma.br/jspui/handle/tede/3683
|
Resumo: |
Hydrothermal scheduling is a relevant stage in the planning of the operation, which the objective is to minimize the total cost of operation during the demand horizon, together with respect for the restrictions of electrical systems such as losses in transmission and the power balance. Concomitantly, efforts are made to reduce dependence on fossil fuels and emission of greenhouse gases from the insertion of alternative sources. In these conditions, this research seeks to present a unit commitment model for smart electrical networks, as well as a methodology based on artificial intelligence techniques. Pumped-storage hydropower are considered, because these systems have the advantage of offering electricity at peak hours from a water storage carried out in upper reservoirs carried out during off-peak hours; thus, they contribute to the reduction of the cost. The proposed methodology is implemented in a MATLAB computational environment and applied to test systems. The analysis of the simulations aims to compare the hydrothermal scheduling cases with and without pumped-storage hydropower plants, in order to search the circumstances of the lowest possible cost. |
