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In Brazil, large consumers have different alternatives to contract energy. The type of contract and its parameters are important decision variables for consumers who aim to reduce their electricity bill. Here, it is proposed a model to assist large consumers to take these decisions. This model is based on a statistic auto regressive (AR) model to forecast monthly energy consumption and maximum demand in order to establish the best contract for the consumer. The performance of the forecast-based model is evaluated through statistical analysis and by comparison with a simpler method that considers the average values. Different contracting environments are investigated. Results show the importance of adequate forecasting in determining the most cost-effective contract strategy.

Energy contracting for large consumers in Brazil: A real case study