Optimization Module for the Electricity Auction Determination
The commercial model of the Brazilian Electricity Sector adopted since 2004 initiated a new type of brought to the area of system operation planning a new methodology for the purchase and sale of electricity.With the inclusion of customers in the free market, there was a need for studies and development of tools for the use of electricity contracting by the industry since a correct choice of energy volume and price can guarantee the company’s profit or the viability of its service. In this sense, the present work presents a module based on open source programming with Java language for computational optimization of the data obtained from the generation of hydroelectric plants and their thermal complementation. Based on artificial intelligence technique, more specifically in the field of genetic algorithms, the same used in the natural selection of species, the program stimulates different scenarios and future possibilities so that through na initial population it is possible to obtain several generations with the best characteristics of each individual and the amount of energy to be distributed between auctions. This in order to mitigate the lack of excess purchases and improve distribution to avoid buying below the necessary demand negotiated by the distribution company. For this, the return of a vector with the best selection of energy distribution in future auctions is then delivered to the end user in order to collaborate with its decision making. The good results obtained with the reduction of overcontracting and subcontracting of the purchase of electricity have demonstrated the feasibility of the program, as well as it can be said that the use of this tool can assist agents in making decisions that lead to minimizing the costs of the business involving energy. Finally, it can be concluded that the risks of future investments can be minimized.