Evaluation of Energy Distribution Using Network Data Envelopment Analysis and Kohonen Self Organizing Maps

Thiago Gomes Leal Ganhadeiro, Eliane Da Silva Christo, Lidia Angulo Meza, Kelly Alonso Costa and Danilo Pinto Moreira de Souza
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Thiago Gomes Leal Ganhadeiro: Postgraduate Program in Computational Modeling in Science and Technology, Fluminense Federal University, Volta Redonda 27255-125, Brazil
Eliane Da Silva Christo: Postgraduate Program in Computational Modeling in Science and Technology, Fluminense Federal University, Volta Redonda 27255-125, Brazil
Lidia Angulo Meza: Postgraduate Program in Production Engineering, Fluminense Federal University, Niterói 24220-900, Brazil
Kelly Alonso Costa: Postgraduate Program in Production Engineering, Fluminense Federal University, Volta Redonda 27255-125, Brazil
Danilo Pinto Moreira de Souza: Postgraduate Program in Computational Modeling in Science and Technology, Fluminense Federal University, Volta Redonda 27255-125, Brazil

Energies, 2018, vol. 11, issue 10, 1-14

Abstract: This article presents an alternative way of evaluating the efficiency of the electric distribution companies in Brazil. This assessment is currently performed and designed by the National Electric Energy Agency (ANEEL), a Brazilian regulatory agency, to regulate energy prices. This involves calculating the X -factor, which represents the efficiency evolution in the price-cap regulation model. The proposed model aims to use a network Data Envelopment Analysis (DEA) model with the network dimension as an intermediate variable and to use Kohonen Self-Organizing Maps (SOM) to correct the difficulties presented by environmental variables. In order to find which environmental variables influence the efficiency, factor analysis was used to reduce the dimensionality of the model. The analysis still uses multiple regression with the previous efficiency as the dependent variable and the four factors extracted from factor analysis as independent variables. The SOM generated four clusters based on the environment and the efficiency for each distributor in each group. This allows for a better evaluation of the correction in the X -factor, since it can be conducted inside each cluster with a maintained margin for comparison. It is expected that the use of this model will reduce the margin of questioning by distributors about the evaluation.

Keywords: data envelopment analysis; Kohonen self-organizing maps; factor analysis; multiple regression; energy efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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