Resumen: This paper proposes a management strategy for the daily operation of an isolated hybrid energy system (HES) using heuristic techniques. Incorporation of heuristic techniques to the optimal scheduling in day-head basis allows us to consider the complex characteristics of a specific battery energy storage system (BESS) and the associated electronic converter efficiency. The proposed approach can determine the discharging time to perform the load peak-shaving in an appropriate manner. A recently proposed version of binary particle swarm optimization (BPSO), which incorporates a time-varying mirrored S-shaped (TVMS) transfer function, is proposed for day-ahead scheduling determination. Day-ahead operation and greenhouse gas (GHG) emissions are studied through different operating conditions. The complexity of the optimization problem depends on the available wind resource and its relationship with load profile. In this regard, TVMS-BPSO has important capabilities for global exploration and local exploitation, which makes it a powerful technique able to provide a high-quality solution comparable to that obtained from a genetic algorithm. Idioma: Inglés DOI: 10.3390/app9235221 Año: 2019 Publicado en: Applied Sciences (Switzerland) 9, 23 (2019), 5221 [30 pp.] ISSN: 2076-3417 Factor impacto JCR: 2.474 (2019) Categ. JCR: PHYSICS, APPLIED rank: 62 / 154 = 0.403 (2019) - Q2 - T2 Categ. JCR: ENGINEERING, MULTIDISCIPLINARY rank: 32 / 91 = 0.352 (2019) - Q2 - T2 Categ. JCR: CHEMISTRY, MULTIDISCIPLINARY rank: 88 / 176 = 0.5 (2019) - Q2 - T2 Categ. JCR: MATERIALS SCIENCE, MULTIDISCIPLINARY rank: 161 / 314 = 0.513 (2019) - Q3 - T2 Factor impacto SCIMAGO: 0.418 - Engineering (miscellaneous) (Q1) - Fluid Flow and Transfer Processes (Q2) - Process Chemistry and Technology (Q2) - Instrumentation (Q2) - Materials Science (miscellaneous) (Q2) - Computer Science Applications (Q3)