Electrical energy prediction study case based on neural networks

2018/03/26 by Cristian Vașar, Octavian Proștean, Vasar, Cristian +5
Computer Science · Engineering · #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Neural Networks and Applications #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1803.09583

openalex publication_date 2018/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper presents some considerations regarding the prediction of the electrical energy consumption. It is well known that the central element of a microeconomic analysis is represented by the economical agents actions, actions that follow their own interest such as: the consumer maximization of his satisfaction, the producer maximization of his profit. The study case is focused on the prediction of the sold energy in Banat region. The goal of this study case is to optimize the electrical energy quantity purchased from the producer by the energy distributor in Banat region. The prediction is based on neural networks. There are used feed-forward and Elman type neural networks. In order to enhance the prediction accuracy there have been used both linear and nonlinear preprocessing units. The aspects considered in this paper can be extrapolated in any general case of prediction based application, not only in the already stated case of electrical energy.

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