Development and application of a software for the energy and exergetic analysis of a fishmeal and fish oil plant
The production of fishmeal and fish oil is essential in the food industry, but it involves high energy consumption and significant thermal losses. This paper presents the development of Python software for the energy and exergy analysis of a fishmeal and fish oil plant. Through computational simulat...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | Perú |
| Institución: | Universidad de San Martín de Porres |
| Repositorio: | Revistas - Universidad de San Martín de Porres |
| Idioma: | español |
| OAI Identifier: | oai:revistas.usmp.edu.pe:article/3077 |
| Acceso en línea: | https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3077 |
| Access Level: | acceso abierto |
| Palabra clave: | Energy analysis, exergy analysis, Python software, fishmeal and fish oil plant, energy efficiency Análisis energético, análisis exergético, software en Python, planta de harina y aceite de pescado, eficiencia energética |
| Sumario: | The production of fishmeal and fish oil is essential in the food industry, but it involves high energy consumption and significant thermal losses. This paper presents the development of Python software for the energy and exergy analysis of a fishmeal and fish oil plant. Through computational simulations, the termal performance of key equipment such as boilers, stoves, dryers and tanks is evaluated. The results indicate that the model is accurate in most of the equipment, with differences of less than 2% in required heat and steam consumption, although discrepancies of 12.03% were identified in the rotadisk dryers, which require adjustments. The energy analysis highlights critical areas for improving energy efficiency. The software provides a comprehensive tool for industrial process optimization and is planned to be expanded with variable load simulations and thermoeconomic analysis to further improve efficiency and reduce operating costs. |
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