This study is concerned with optimizing the daily operation of a solar power plant equipped with thermal energy storage system (TES). The modeling is performed by solving a set of non-linear governing equations and is verified through comparison with the literature. "Maximum production period" and "maximum revenue" constitute the objectives of the optimization study which are first considered individually (as two single-objective problems) and are then considered simultaneously (as a multi-objective problem). Genetic Algorithm (GA) is employed as the optimization tool. The results of the first objective (maximum production period) shows 7 hours increase in the daily production time as a result of employing the TES system. This occurred through saving energy during the times of high solar radiation and using the stored energy for electricity generation during the times of low or zero solar radiation. The results of the second objective (maximum revenue) indicate 13.5% increase in the produced profit as a result of employing the TES system. This improvement was resulted from saving energy during the times of low electricity price and using the stored energy for maximum electricity generation during the times of high electricity price. Finally, in the multi-objective study, 5 hours increase in the production period and 8.1% increase in the revenue were simultaneously obtained as a result of a proper tradeoff between the two objectives.