Decision support system for the management of electricity consumption contracts for Smart Grids environment using Differential Evolution and Artificial Neural Network

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.