Evaluación de la generación fotovoltaica de un sistema autónomo optimizando su abastecimiento ante la variación de la radiación.

This research work, the photovoltaic generation of an autonomous system is determined to optimize the supply of the loads through a genetic algorithm and minimize the consumption of the system. First, the parameters that intervene in the autonomous photovoltaic system are defined, such as: inclination of the panels, azimuth, distance between panels (racks), performance index (Performance Ratio - PR), peak solar time (PSH) and performance of photovoltaic energy. Next, the object function and restrictions are established, seeking to minimize the consumption of the system taking into account the installed loads and as a restriction the load census in the company Genim S.A. For optimization, the genetic algorithm method is used, complying with the population generation operators, selection of individuals, crossing, mutation, new population generation and the stopping criterion, finding the optimal operating hours of the loads. The algorithm was implemented within the Matlab computational tool, consequently the following optimal hours of operation of the loads are: motor 1 (M1) works 9 hours, motor 2 (M2) works 4 hours, motor 3 (M3) works 8 hours , engine 4 (M4) runs 6 hours, engine 5 (M5) runs 9 hours and engine 6 (M6) runs 7 hours. In general, the solutions found by the implemented genetic algorithm are considered good since daily consumption is minimized by 1.65 kWh.

• Hovedforfatter: Chancusig López, Marcelo Bernave (author)
• Format: masterThesis
• Sprog: spa
• Udgivet: 2021
• Fag: SISTEMA FOTOVOLTAICO AUTÓNOMO; ALGORITMO GENÉTICO; ELECTRICIDAD
• Online adgang: http://repositorio.utc.edu.ec/handle/27000/8012