Detalhes bibliográficos
Ano de defesa: |
2012 |
Autor(a) principal: |
CERQUEIRA JÚNIOR, Sidney Nascimento
![lattes](/bdtd/themes/bdtd/images/lattes.gif?_=1676566308) |
Orientador(a): |
SAAVEDRA MENDEZ, Osvaldo Ronald |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
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Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Universidade Federal do Maranhão
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Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
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Departamento: |
DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
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País: |
Brasil
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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: |
http://tedebc.ufma.br:8080/jspui/handle/tede/1809
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Resumo: |
In the last years, the process of restructuring of the electricity market, brought several changes in the operational e regulatory aspects. The main idea was the separation of the generation, transmission and distribution activities in order to insert the competition among them, aimed to increase the e ciency, safety and quality of supply of electrical energy. The hourly schedule, usually called a Unit Commitment has as objective the de - nition of which generators should be online/o ine and their respective operation points. In some markets based on this new model, the determination of the optimal scheduling of generators (thermal and hydro) is made by the Agent Generator, which is largely responsible for the allocation of your portfolio. Given this, the aim of this work is to nd the operational policy that will maximize the pro t of Agent Generator, based on forecast price and respecting the thermal, hydro and market constrictions assigned to the problem. Thus, the optimal schedule found is an important factor in developing strategies to o ers of bids to auctions in which the Genco will participate. For the case study technique Particle Swarm Optimization is applied to solve the problem in plants belonging to the Brazilian electric system, which are also analyzed the in uence of the start-up cost to the optimal schedule. |