Application of stochastic programming and probabilistic analyses as key parameters for real decision making regarding implementing or not energy rationing - a case study for the Brazilian hydrothermal interconnected system

During 2014 and 2015, the Brazilian hydrothermal interconnected system faced critical hydrological conditions, such as extremely low multivariate inflow values on February 2014 and January 2015. Therefore, an issue that arose in early 2014 was whether the Brazilian government would have to implement or not an energy rationing. In this sense, this paper summarizes a proposed approach to technically support this decision, based on dual stochastic dynamic programming, multivariate inflows scenarios generation and probabilistic analyses, and that utilized the chain of optimization models developed by CEPEL and real configurations of the Brazilian large scale interconnected hydrothermal system. These studies, inserted in a very comprehensive and detailed technical analyses carried out by the Brazilian Monitoring Committee of the Electrical Sector, led to the decision of not implementing an energy rationing in 2014, and to continue to closely monitoring the electric power system performance.