Systemic model for the analysis of residential energy consumption scenarios

This paper presents the methodology and development of a systemic model, built using the systems dynamic methodology, for the analysis of energy consumption scenarios by air conditioning in the residential sector. The model allows to analyze the total energy consumption of homes and disaggregated by...

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Autores principales: Barbero, Dante Andrés; Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad Nacional de La Plata. Facultad de Arquitectura y Urbanismo, Chévez, Pedro Joaquín; Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad Nacional de La Plata. Facultad de Arquitectura y Urbanismo, Discoli, Carlos Alberto; Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad Nacional de La Plata. Facultad de Arquitectura y Urbanismo, Martini, Irene; Consejo Nacional de Investigaciones Científicas y Técnicas. Universidad Nacional de La Plata. Facultad de Arquitectura y Urbanismo
Formato: Artículo revista
Lenguaje:Español
Publicado: Universidad Nacional del Nordeste. Facultad de Arquitectura y Urbanismo 2022
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Acceso en línea:https://revistas.unne.edu.ar/index.php/crn/article/view/5958
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Sumario:This paper presents the methodology and development of a systemic model, built using the systems dynamic methodology, for the analysis of energy consumption scenarios by air conditioning in the residential sector. The model allows to analyze the total energy consumption of homes and disaggregated by equipment applying efficiency measures. For the modeling of the consumption for cooling and heating, different equipment was taken into account considering for each one: the quantity, nominal powers, labeling levels according to current norms and the average hours of use. Likewise, the possibility of analyzing different energy efficiency measures was included in the model. The developed model allows analyzing the temporal evolution of the disaggregated and total energy demand of the building equipment, allowing to compare, through sensitivity analysis, different possible scenarios from the adoption of various technological and energy efficiency measures.