bachelorThesis
Método autorregresivo arima para una previsión de carga residencial a corto plazo basado en el aprendizaje del comportamiento de los clientes residenciales
Fecha
2022-05Autor
Lora Arias, Luis Eduardo
Institución
Resumen
In the present titling work, it is intended to foresee the load behavior of residential clients. Implementing an ARIMA autoregressive forecasting model, based on data established by a smart meter, knowing residential consumption in a set time and diagnosing an expansion solution to meet residential demand. Once Validated the data implemented by using a database of an Iot cloud to MATLAB, we in the load profile of residential electricity. Once the solution is implemented, through the validation and verification of this method, the total load obtained in a short period of time is taken into account, and the need or not of an expansion to satisfy the demand that covers a residential sector is determined.