TY - JOUR
T1 - Energy Optimization in Hotels
T2 - Strategies for Efficiency in Hot Water Systems
AU - Valdivia Nodal, Yarelis
AU - Iturralde Carrera, Luis Angel
AU - Zapatero-Gutiérrez, Araceli
AU - Guerra Plasencia, Mario Antonio Álvarez
AU - Reyes Calvo, Royd
AU - Álvarez-Alvarado, José M.
AU - Rodríguez-Reséndiz, Juvenal
N1 - Publisher Copyright:
© 2025 by the authors.
PY - 2025/6/1
Y1 - 2025/6/1
N2 - This paper presents a procedure for the energy optimization of domestic hot water (DHW) systems in hotels located in tropical climates that use centralized air conditioning systems. The study aims to maximize heat recovery from chillers and reduce the fuel consumption of auxiliary heaters by optimizing operational variables such as water mass flow in the primary and secondary DHW circuits and outlet temperature of the backup system. The optimization is implemented using genetic algorithms (GA), which enable the identification of the most efficient flow configurations under variable thermal demand conditions. The proposed methodology integrates a thermoenergetic model validated with real operational data and considers the dynamic behavior of hotel occupancy and water demand. The results show that the optimized strategy reduces auxiliary heating use by up to 75%, achieving annual energy savings of 8244 kWh, equivalent to 2.3 tons of fuel, and preventing the emission of 10.5 tons of CO2. This study contributes to the design of sustainable energy systems in the hospitality sector and provides replicable strategies for similar climatic and operational contexts.
AB - This paper presents a procedure for the energy optimization of domestic hot water (DHW) systems in hotels located in tropical climates that use centralized air conditioning systems. The study aims to maximize heat recovery from chillers and reduce the fuel consumption of auxiliary heaters by optimizing operational variables such as water mass flow in the primary and secondary DHW circuits and outlet temperature of the backup system. The optimization is implemented using genetic algorithms (GA), which enable the identification of the most efficient flow configurations under variable thermal demand conditions. The proposed methodology integrates a thermoenergetic model validated with real operational data and considers the dynamic behavior of hotel occupancy and water demand. The results show that the optimized strategy reduces auxiliary heating use by up to 75%, achieving annual energy savings of 8244 kWh, equivalent to 2.3 tons of fuel, and preventing the emission of 10.5 tons of CO2. This study contributes to the design of sustainable energy systems in the hospitality sector and provides replicable strategies for similar climatic and operational contexts.
KW - domestic hot water systems
KW - energy efficiency
KW - energy optimization
KW - heat recovery
UR - http://www.scopus.com/inward/record.url?scp=105009299210&partnerID=8YFLogxK
U2 - 10.3390/a18060301
DO - 10.3390/a18060301
M3 - Artículo
AN - SCOPUS:105009299210
SN - 1999-4893
VL - 18
JO - Algorithms
JF - Algorithms
IS - 6
M1 - 301
ER -