Title :
Decision support system for the management of electricity consumption contracts for Smart Grids environment using Differential Evolution and Artificial Neural Network
Author :
Matte Freitas, Daniel ; Pereira Pinto, Joao Onofre ; Godoy, R.B. ; Galotto, Luigi ; Ribeiro, P.E.M.J. ; Pinto, Alexandra M. A. C.
Author_Institution :
BATLAB, Fed. Univ. of Mato Grosso do Sul, Campo Grande, Brazil
Abstract :
The objective of this paper is to present a support system to manage electricity consumption contracts for Smart Grid environment. The system modeling uses historical data consumption and energy trading rules to find the optimal contract structure. Focused Time Lagged Feed forward Network was used to model the historical data. The global search tool Differential Evolution was used to find the best contract structure. This paper presents the use of the tool with current Brazilian pricing rules. However, to change the rules for a dynamic scenario of Smart Grid can be easily implemented. The results are satisfactory and indicate the feasibility of the system for different cases.
Keywords :
decision support systems; electrical contracting; energy consumption; evolutionary computation; feedforward neural nets; power engineering computing; power system management; search problems; smart power grids; Brazilian pricing rules; artificial neural network; best contract structure; decision support system; differential evolution; electricity consumption contracts; energy trading rules; focused time lagged feed forward network; global search tool; historical data consumption; optimal contract structure; smart grids environment; system modeling; Contracts; Electricity; Neurons; Smart grids; Sociology; Statistics; Vectors;
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
DOI :
10.1109/IECON.2013.6700398
