Abstract—Predominantly, hydroelectric power fuels Colombia’s electricity. Yet, non-interconnected zones, mainly in the Pacifico, Orinoquia, Amazonia, and insular regions, rely primarily on diesel power plants. This research presents an optimisation model for integrating Renewable Energy Sources (RES) in San Andres Island, Colombia. A bi-level, multi-objective optimisation strategy is employed, developed on MATLAB. Utilizing a particle swarm multi-objective algorithm, the model synergizes planning/design with operational aspects. Solutions are assessed via Key Performance Indicators (KPIs), considering renewable sources such as solar, wind, battery storage, electrolysers, hydrogen storage, and fuel cells. Remarkably, 78 out of 80 results from the four case studies retained diesel generation, battery storage was mainly excluded, and wind emerged as the dominant renewable source.

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.

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