dc.contributorSalgado Rodríguez, Modesto Enrique
dc.contributorPatiño Chitacapa, César Andrés
dc.creatorMontalvan Delgado, Joel Alejandro
dc.creatorMorales Jadan, Rommel Eduardo
dc.date.accessioned2019-12-18T19:24:58Z
dc.date.accessioned2022-10-20T22:25:13Z
dc.date.available2019-12-18T19:24:58Z
dc.date.available2022-10-20T22:25:13Z
dc.date.created2019-12-18T19:24:58Z
dc.date.issued2019-12-18
dc.identifierhttp://dspace.ucuenca.edu.ec/handle/123456789/33753
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4610227
dc.description.abstractThe next work presents the development and application of models focused on load forecasting through trend and simulation in order to solve the medium and large issues of the electric distribution system of the “Empresa Eléctrica Regional Centro Sur C.A”. The trend-focused model will use Matlab's tools such as Fuzzy Logic (FL) and Artificial Neuronal Networks (ANN) relating variables such as GNP, customers and population with energy consumption, making use of its records to project new consumption. The result of the trend model is compared with the load forecast made by the distribution company using the Holt Winter method. The simulation model will focus only on the urban areas of Cuenca for residential customers, using the programming language Python, to create a probability map by training a neural network that analyzes the evolution of spatial factors of proximity, environmental and local in a temporary way at the geographical grid level. To later disaggregate the global load forecasting of customers in each suitable grid categorized by means of the mathematical model known as Cellular Automata (CA), which is responsible for assigning new customers, and then converting this increment of customers into power demand for the load forecasting at 2033.
dc.languagespa
dc.publisherUniversidad de Cuenca
dc.relationTE;468
dc.subjectIngeniería Eléctrica
dc.subjectInteligencia artificial
dc.subjectDeep learning
dc.subjectProbabilidades
dc.titleProyección espacial de la demanda en la Empresa Regional Centrosur C.A, mediante métodos heurísticos
dc.typebachelorThesis


Este ítem pertenece a la siguiente institución