Dynamic Simulation and Heuristic Optimization of a Solar Tracking Photovoltaic System for Reducing Electricity Consumption in a University Institution in Cartagena, Colombia

This study proposes a dynamic simulation and heuristic optimization methodology to evaluate the integration of solar tracking photovoltaic systems in a university institution located in Cartagena de Indias, Colombia. The energy baseline was established using a real electricity bill, with a monthly consumption of 22,880 kWh and a total cost of COP 17,470,020. Since only one institutional electricity bill was available at this preliminary stage, an estimated annual consumption series was generated using monthly variation factors associated with academic activity dynamics. Solar radiation and daily ambient temperature data were obtained from the NASA POWER database for the geographical coordinates of Cartagena. Three configurations were simulated: a fixed photovoltaic system, a single-axis solar tracking system, and a dual-axis solar tracking system. The model incorporated cell temperature thermal correction, dynamic performance ratio, tracking factors, economic savings, and CO₂ emission reductions. Additionally, a genetic algorithm was applied to estimate the required installed capacity under a predefined energy coverage target. The results show that a 100 kWp dual-axis tracking system could cover approximately 58.53% of the estimated annual demand, while the heuristic optimization identified an installed capacity of 85.43 kWp to achieve 50% demand coverage. These results suggest that solar tracking photovoltaic systems can represent a viable alternative for improving energy sustainability in tropical university campuses.