This research studies a general modeling to evaluate different scenarios of travel patterns and their impact on the daily cost negotiated in the Real Time and Day-Ahead market, using the GAMS methodology in a MILP model, evaluating also a characterization of the PQP market (price quantity probability). The purpose of this characterization is to determine the behavior of the electric energy market, considering also the deterioration of batteries and the negotiations of it in real time in situations of shortage and overload, optimizing in this way the effects of the analysis of the cost of the application of the battery on the different travel patterns, consequently triggering the emergence of the development of the local electric transport aggregator industry.