Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities

The concept of Economically Adapted Distribution System, is based on the Neo-Classic Economics Paradigm. It is related only to the productive efficiency, which implies the expansion and operation of system with a minimum cost. It ignores the uncertainties, or it renders them a stochastic nature, whi...

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Autores principales: Shweickardt, Gustavo, Miranda, Vladimiro, Gimenez, Juan Manuel
Formato: Artículo revista
Lenguaje:Español
Publicado: Escuela de Perfeccionamiento en Investigación Operativa 2018
Materias:
adaptación económica
análisis de riesgo
optimización multicriterio
sistemas de distribución de energía eléctrica
economic adaptation
risk analysis
multicriteria optimization
electric distribution systems
Acceso en línea:https://revistas.unc.edu.ar/index.php/epio/article/view/20346
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Revista de la Escuela de Perfeccionamiento en Investigación Operativa de Universidad Nacional de Córdoba
id I10-R359-article-20346
record_format ojs
spelling I10-R359-article-203462018-06-18T15:15:55Z Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities Control de la adaptación económica en sistemas de distribución de energía eléctrica mediante un modelo posibilistico de optimización dinámica. Parte I: modelos de preferencias bajo incertidumbres y de optimización posibilistica Shweickardt, Gustavo Miranda, Vladimiro Gimenez, Juan Manuel adaptación económica análisis de riesgo optimización multicriterio sistemas de distribución de energía eléctrica economic adaptation risk analysis multicriteria optimization electric distribution systems The concept of Economically Adapted Distribution System, is based on the Neo-Classic Economics Paradigm. It is related only to the productive efficiency, which implies the expansion and operation of system with a minimum cost. It ignores the uncertainties, or it renders them a stochastic nature, which they do not necessarily show to have. In this work, a model to evaluate the Deadaptation System degree, in the regulatory control periods, is presented.The model, based in Multicriteria Optimization and non stochastic incertainties, suggest a change of paradigm from the approach of Incertainty and Risk proposed by Pos-Keynesianism. A strong difference between Static Optimization respect to Non Stochastic Dynamic, proposed in the Posibilistic Model, and a complete and new theoretical development, for application in a real Case of Study, are presented as important results and conclusions of this work. In this First part of work, the development of Preferences Model under uncertainties and Dynamic Possibilistic Optimization Model, are presented. El concepto de Sistema de Distribución Económicamente Adaptado, se sustenta en el Paradigma Económico Neo-Clásico, referido en el estado del arte como dominante. Se lo vincula sólo a la eficiencia productiva que implica la expansión y operación del sistema a mínimo costo. Ignora las incertidumbres o bien se les confiere un carácter estocástico que no necesariamente exhiben. En este trabajo se presenta un modelo alternativo para evaluar el grado de desadaptación del sistema, en los períodos de control tarifario fijados regulatoriamente.El modelo, sustentado en la optimización dinámica multicriterio bajo condiciones de incertidumbres no estocásticas, es solidario a un paradigma diferente, desde la visión de Riesgo e Incertidumbre propuesta por el Pos-Keynesianismo. Se aportan, como resultados más relevantes, una marcada diferenciación entre la Optimización Estática, sustentada en los métodos clásicos asociados al Paradigma Dominante, respecto de la Dinámica no Estocástica propuesta en el Modelo Posibilístico, así como un completo y novedoso desarrollo teórico para su aplicación sobre un estudio de caso real. En la Primera parte del trabajo, se presentan los desarrollos relativos al Modelo de Preferencias bajo Incertidumbres y al de Optimizacíon Dinámica Posibilística. Escuela de Perfeccionamiento en Investigación Operativa 2018-06-18 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/epio/article/view/20346 Revista de la Escuela de Perfeccionamiento en Investigación Operativa; Vol. 20 Núm. 33 (2012): Octubre; 89-111 1853-9777 0329-7322 spa https://revistas.unc.edu.ar/index.php/epio/article/view/20346/19977
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-359
container_title_str Revista de la Escuela de Perfeccionamiento en Investigación Operativa
language Español
format Artículo revista
topic adaptación económica
análisis de riesgo
optimización multicriterio
sistemas de distribución de energía eléctrica
economic adaptation
risk analysis
multicriteria optimization
electric distribution systems
spellingShingle adaptación económica
análisis de riesgo
optimización multicriterio
sistemas de distribución de energía eléctrica
economic adaptation
risk analysis
multicriteria optimization
electric distribution systems
Shweickardt, Gustavo
Miranda, Vladimiro
Gimenez, Juan Manuel
Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
topic_facet adaptación económica
análisis de riesgo
optimización multicriterio
sistemas de distribución de energía eléctrica
economic adaptation
risk analysis
multicriteria optimization
electric distribution systems
author Shweickardt, Gustavo
Miranda, Vladimiro
Gimenez, Juan Manuel
author_facet Shweickardt, Gustavo
Miranda, Vladimiro
Gimenez, Juan Manuel
author_sort Shweickardt, Gustavo
title Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
title_short Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
title_full Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
title_fullStr Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
title_full_unstemmed Control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. Part I: preference models under uncertainties and optimization possibilities
title_sort control of the economic adaptation in electrical energy distribution systems by means of a dynamic optimization model. part i: preference models under uncertainties and optimization possibilities
description The concept of Economically Adapted Distribution System, is based on the Neo-Classic Economics Paradigm. It is related only to the productive efficiency, which implies the expansion and operation of system with a minimum cost. It ignores the uncertainties, or it renders them a stochastic nature, which they do not necessarily show to have. In this work, a model to evaluate the Deadaptation System degree, in the regulatory control periods, is presented.The model, based in Multicriteria Optimization and non stochastic incertainties, suggest a change of paradigm from the approach of Incertainty and Risk proposed by Pos-Keynesianism. A strong difference between Static Optimization respect to Non Stochastic Dynamic, proposed in the Posibilistic Model, and a complete and new theoretical development, for application in a real Case of Study, are presented as important results and conclusions of this work. In this First part of work, the development of Preferences Model under uncertainties and Dynamic Possibilistic Optimization Model, are presented.
publisher Escuela de Perfeccionamiento en Investigación Operativa
publishDate 2018
url https://revistas.unc.edu.ar/index.php/epio/article/view/20346
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first_indexed 2024-09-03T22:23:17Z
last_indexed 2024-09-03T22:23:17Z
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