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This paper presents the application of the Particle Swarm Optimization (PSO) algorithm to optimize the configuration of photovoltaic (PV) panels, wind turbines (WT), and battery energy storage systems (BESS) to meet an average power demand. Detailed electrical and mathematical models of PV generation, WT systems, and energy storage are developed and integrated into the optimization framework. The study utilizes solar irradiance and wind speed data from two locations in Ecuador: Aromo and Arenal, considering two specific hardware configurations. The optimization results were statistically validated through 30 simulation runs for each location and proposed scenarios. Subsequently, the optimized configurations were evaluated using the complete power demand profile. The final results provide optimized solutions to minimize implementation costs or power losses, depending on available energy resources and hardware configurations.

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Sizing Optimization of Off-Grid Solar-Wind Based Energy Generation Systems in Ecuador Considering Techno-Economic Constraints on a PSO Algorithm

  • 会议论文

  • 发表日期：

    2026年

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  • Jorge Hernandez-Ambato,
  • Betty Tacuri-Sanchez,
  • Ramiro Isa-Jara,
  • Victor Herrera-Perez

摘要

This paper presents the application of the Particle Swarm Optimization (PSO) algorithm to optimize the configuration of photovoltaic (PV) panels, wind turbines (WT), and battery energy storage systems (BESS) to meet an average power demand. Detailed electrical and mathematical models of PV generation, WT systems, and energy storage are developed and integrated into the optimization framework. The study utilizes solar irradiance and wind speed data from two locations in Ecuador: Aromo and Arenal, considering two specific hardware configurations. The optimization results were statistically validated through 30 simulation runs for each location and proposed scenarios. Subsequently, the optimized configurations were evaluated using the complete power demand profile. The final results provide optimized solutions to minimize implementation costs or power losses, depending on available energy resources and hardware configurations.