This paper focuses on modeling power exchanges in a multi-agent interacting framework with reduced behavioral assumptions. A model of the day ahead market session of OMEL (the Spanish Power Exchange) is proposed using real demand data with simulated seller strategies. The number of sellers is defined at the first stage and the quantity of goods is distributed over the population of agents according to several initial distributions. A Clearing-house mechanism matches the cumulative demand and supply curves in order to determine the market-clearing price. The resulting price time-series are statistically tested to verify the validity of the model. Results show the main properties of real market and assess the validity of the proposed model.