Resumen: In this work, the short term (daily) operation of an off-grid hybrid PV-diesel-battery system is optimized by genetic algorithms. An integer variable (0, 1 or 2) for each hour of the day decides the way the battery works. With the forecast of the hourly irradiation, temperature and load consumption for the next day, and estimating the state of charge of the battery (SOC) at the first hour of the day, we perform the optimization of the integer variables for the 24 hours of next day. To avoid inadmissible computation time, the optimization is performed by using genetic algorithms (GA) obtaining in roughly 1 hour the optimal solution or a solution near the optimal one. The optimization tries to obtain the minimal total cost of the daily operation while supplying the whole load. We compare the results of the optimization with the typical control strategies (load following, cycle charging and set point strategies), obtaining better results with the new optimized strategy. The reduction in the operational cost obtained varies from 2.5% to 62%, compared to the typical control strategies (load following or cycle charging). Idioma: Inglés DOI: 10.24084/reepqj24.395 Año: 2024 Publicado en: Renewable Energies, Environment & Power Quality Journal 2 (2024), 233-239 ISSN: 3020-531X Financiación: info:eu-repo/grantAgreement/ES/AEI/PID2021-123172OB-I00 Tipo y forma: Artículo (Versión definitiva) Área (Departamento): Área Ingeniería Eléctrica (Dpto. Ingeniería Eléctrica)