Original scientific paper
https://doi.org/10.30765/er.1529
A computational approach to forecasting and minimizing electricity costs in the short-term market for distributors in Brazil
Francisco E. Bezerra
; Industrial Engineering Graduate Program, Universidade Nove de Julho, Rua Vergueiro, Liberdade, São Paulo – Brazil
Luis C. Santos Jr
; Informatics and knowledge management Graduate Program, Universidade Nove de Julho, Rua Vergueiro, Liberdade, São Paulo – Brazil
Cleber G. Dias
; Informatics and knowledge management Graduate Program, Universidade Nove de Julho, Rua Vergueiro, Liberdade, São Paulo – Brazil
Fabio H. Pereira
; Industrial Engineering Graduate Program, Universidade Nove de Julho, Rua Vergueiro, Liberdade, São Paulo – Brazil, Informatics and knowledge management Graduate Program, Universidade Nove de Julho, Rua Vergueiro, Liberdade, São Paulo – Brazil
Abstract
In Brazil, the electric power distributors must buy electricity on auctions one, three and five years ahead. If there is inefficiency in the contracting of electric energy, the chamber of Commercialization of Electric Energy, which enables the commercialization, can apply penalties. Thus, this paper proposes a computational approach to forecasting electricity by the class of the consumer using a multi-layer perceptron artificial neural network with a backpropagation algorithm and a prediction using time series techniques through the Bayesian and Akaike selection criteria. The forecast of electricity consumption can serve as support in the purchase of electricity in auctions in the regulated contracting environment and in the process of settlement of differences and for energy management, customer service, and distributor billing. The results show that a multilayer network with a backpropagation algorithm is able to learn the behavior of the data that influences the electric energy consumed by consumption class and can be used to follow the evolution in the demand of each class of consumption and, consequently, to help distributors in the process of contracting of electricity, reduce losses like fines, and reduce the costs of the energy distributor.
Keywords
power distributor; commercialization of electric energy; forecasting electricity; multilayer network.
Hrčak ID:
247934
URI
Publication date:
20.12.2021.
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