EN
ES
Título:
Electrical Energy Consumption Forecast Using Support Vector Machines.
Electrical Energy Consumption Forecast Using Support Vector Machines.
Autores:
Vinagre, Eugénia; Pinto, Tiago; Ramos, Sergio; Vale, Zita; Corchado Rodríguez, Juan M.
Libro:
Database and Expert Systems Applications (DEXA), 2016 27th International Workshop on. pp. 171-175.
Fecha de Publicación:
2016
ISSN:
2378-3915
Smart Grid (SG) concept is defined as an electricity network operated intelligently to integrate the behavior and actions of all energy resources connected to the network to ensure efficient, sustainable, economic and secure supply of electricity. This concept emerged in recent decades not only for economic reasons but also ecological and even political. SG have been the subject of major studies and investments and continues to represent an area of enormous challenges. Some of the problems of intelligent systems connected to the managed SG are: the real-time processing optimization algorithms and demand response programs; and more accurate predictions in the management of production and consumption. This paper presents a case study for evaluating the performance and accuracy of energy consumption forecast with use of SVM (Support Vector Machines) in different frameworks