Operation of the argentinean interconnected electricity network
A methodology to select optimally the electricity generation plants of the Argentinian interconnected network is developed. The electricity generation grid has different fossil fuel, hydroelectric and nuclear power stations. The power plants configuration connected to die grid and their operating lo...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2009 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/62691 |
| Acceso en línea: | http://hdl.handle.net/11336/62691 |
| Access Level: | acceso abierto |
| Palabra clave: | Cost Greenhouse Emissions Interconnected Electricity Network Operation https://purl.org/becyt/ford/2.4 https://purl.org/becyt/ford/2 |
| Sumario: | A methodology to select optimally the electricity generation plants of the Argentinian interconnected network is developed. The electricity generation grid has different fossil fuel, hydroelectric and nuclear power stations. The power plants configuration connected to die grid and their operating loads are selected minimizing life cycle greenhouse gas emissions and operating cost simultaneously. A life cycle approach to estimate greenhouse gas emissions of thermoelectric, hydroelectric and nuclear power plants is followed. Binary operating variables represent discrete decisions to select which power plant is connected to the grid and the type of fossil fuel used. Continuous operating variables are introduced to select the optimal load for each power plant. A mixed integer linear programming problem is formulated and solved in GAMS. Significant reductions in green house emissions and operating cost are achieved simultaneously in the operation of die electricity network. Thus, a useful tool to support a decision-making process in the operation of a key energy sector is presented. © 2009 Elsevier B.V. All rights reserved. |
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