Aplicación de algoritmos de aprendizaje automático para identificar patrones de las variables ambientales y eléctricas de la central solar de la UTPL

Abstract

Abstract: The present degree work was based on the development of an application based on Machine Learning Algorithms specifically Kmeans, for the process of identifying Patterns of the Environmental and Electrical Variables of the UTPL Solar Power Plant for decision making by the authorities of University. In the development of the project, a series of data collection techniques and instruments were used, specifically the analysis of sources from the solar panel manufacturer, direct observation and interviews. To fulfill the objectives, the Python language, Machine Learning Algorithms, is used, as well as a web application is created using Django for cleaning, data processing and creation of graphics. In this way, after processing the data and viewing the graphs, very important patterns can be deduced to better understand the benefit of using the Solar Power Plant of the Private Technical University of Loja.