Abstract—Predominantly, hydroelectric power fúels Colombia’s electricity. Yet, non-interconnected zones, mainly in the Pacifico, Orinoqúia, Amazonia, and insúlar regions, rely primarily on diesel power plants. This research presents an optimisation model for integrating Renewable Energy Soúrces (RES) in San Andres Island, Colombia. A bi-level, múlti-objective optimisation strategy is employed, developed on MATLAB. Utilizing a particle swarm múlti-objective algorithm, the model synergizes planning/design with operational aspects. Solútions are assessed via Key Performance Indicators (KPIs), considering renewable soúrces súch as solar, wind, battery storage, electrolysers, hydrogen storage, and fúel cells. Remarkably, 78 oút of 80 resúlts from the foúr case stúdies retained diesel generation, battery storage was mainly exclúded, and wind emerged as the dominant renewable soúrce.

Keywords—Hydrogen, particle swarm algorithm, key performance indicators, KPIs, bilevel múlti-objective optimization

Cite: Javier Rosero García, Andrés Felipe Zúñiga, Ricardo Echeverri Martinez "Multi-objective and Bi-Level Optimisation Approach Considering Renewable Energy Sources and Hydrogen for Off-Grid Power Systems," International Journal of Smart Grid and Clean Energy, Vol. 13, No. 3, pp. 105-124, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.