In this paper a scheduling optimization framework is developed to enhance power plants operational decision making process. The proposed framework optimizes plant schedule including operating conditions and maintenance intervals simultaneously and on an hourly basis. In a long term operation plant performance deteriorates due to components aging. This study employs equivalent operating hour (EOH) approach to describe components aging impact on the plant performance deterioration and consequently plant long term profit. Modeling of components aging increases system simulation accuracy in long term operation and the optimum decision variables would be more reliable and realistic. Validity and usefulness of the proposed methodology are demonstrated by optimizing the operating conditions and maintenance intervals of a gas turbine power plant, under different seasonal ambient conditions and energy prices. The case study results effectively meet all the positive expectation that are placed on the proposed aging based optimal scheduling framework. Results show that optimal operation schedule depends on the maintenance intervals. Therefore, operating conditions and maintenance intervals should be optimized simultaneously. In addition, derived optimal schedule increases the system's long term profit approximately 4% annually in comparison with a case that operates at optimal schedule without considering the aging effects in the optimization procedure.