Estimación de la demanda eléctrica de la cocina de inducción por análisis clúster. - Camacho Ortega, Leoncio Francisco (2017)
The present work of thesis has as main objective to realize the estimation of the electrical demand of an induction cooktop by cluster analysis. The electric power consumption of the induction cooktop was monitored to five residential users in the city of Loja, the measurement period comprises from March 1 to June 30, 2016. In order to carry out the measurement campaign, instant energy meter Efergy E2 Classic was used, this equipment allowed to censor the energy consumption of the induction cooktops expressed in kWh per hour in daily and monthly form. Once the database was obtained, a classification and evaluation of the same was done applying the data mining. For the estimation of the electrical demand, three methods of cluster analysis were used, Dendrogram Method, K-Means and Fuzzy C-Means. These methods were used from the Matlab® Toolbox. In the cluster analysis we proceeded to group the data of electrical consumption in two clusters for each user, obtaining a characteristic electrical consumption curve for each cluster. From the cluster analysis it was determined that of the five users analyzed, three present a consumption that has similar characteristics to each other, it was established that the maximum value of electric energy consumption of these three users is 0.518 kWh, with a maximum power of 2,307 kW on working days (Monday to Friday), while the maximum value of electric consumption of weekends (Saturday and Sunday) is 0.344 kWh, with a maximum power of 2,684 kW. The two remaining users present a different clusters, this due to the habits of use of the induction cooktop. Finally, an algorithm was implemented to perform cluster analysis, a Graphical User Interface (GUI) was developed in Matlab®, this application allows to perform the cluster analysis applying the three techniques used in this work, in addition the evaluation of the grouping is realized using the Ward's method that has been implemented in the Dendrogram technique. The developed algorithm calculation response is immediate, which allows to visualize the results obtained for each analysis technique, as well as facilitates the user to manage the results.