Análise de oportunidades de poligeração em edificações e cidades
Distributed generation in buildings and cities has been proposed as an important option for countries in order to include more technologies in their energy mixes. In Brazil, the possibility of including distributed generation in buildings has recent advances in energy policy and building energy effi...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.unesp.br:11449/137978 |
| Acceso en línea: | http://hdl.handle.net/11449/137978 |
| Access Level: | acceso abierto |
| Palabra clave: | Polygeneration Optimization Thermal systems Distributed generation Poligeneración Optimización Generación distribuida Poligeração Otimização Sistemas térmicos Geração distribuida |
| Sumario: | Distributed generation in buildings and cities has been proposed as an important option for countries in order to include more technologies in their energy mixes. In Brazil, the possibility of including distributed generation in buildings has recent advances in energy policy and building energy efficiency standards. For these reasons, new construction projects of sustainable buildings include the assessment of distributed generation in the initial stages. In this work, we present an approach for attending energy needs (steam, hot water, cooling and electricity) of a hospital. The information about demand is classified in eight typical days, two for each season of the year (autumn, winter, spring and summer); a workday and a weekend day. The approach consists in the optimization of a superstructure containing different energy generation and cogeneration technologies like solar panels, for obtaining the best configuration in economic terms. The superstructure is flexible, this is, it allows buying or selling electricity. It also analyzes three cases, verifying the feasibility for generating more electricity. Finally, the results present the final configuration obtained from the optimization process. |
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