A large-scale intelligent control system for the combined transmission of wind power and thermal power comprises a control center station, a control master station, a control substation, a wind farm control execution station and a thermal power plant control execution station, wherein the control center station is connected with the control master station through a special fiber channel; the control master station is connected with the control substation through a special fiber channel; and the control master station is connected with the control execution stations through a special fiber channel. A central processing unit of the control center station is installed with active power optimization method software for achieving the combined transmission of the wind power and the thermal power. Using the existing commercial software, the method can calculate the active power requirement of the section for combined transmission of the wind power and the thermal power in each operation period under various kinds of operation modes so as to reasonably arrange the planned power curve of units. During operation, the method can send the active power requirement of the section according to the ultra-short period wind power prediction result in each fixed period, and can optimize the power generation capacity of the wind power units and the thermal power units while considering the regulation characteristics of the wind power units and the thermal power units. The method can effectively reduce the active power fluctuations, which facilitates the safety and stability of the system so as to maximally utilize the wind power.