This paper describes the construction of an Intelligent System for Operation Planning (ISOP) in heating, ventilating, and air conditioning (HVAC) processes. The system contains important expertise, qualitative reasoning, and quantitative computation. It is used to assist or train operators to achieve better operation in HVAC systems. Expertise about operation planning is expressed as air enthalpy, and moisture conditions and air supply are considered as dynamic parameters. Therefore, it provides a real-time integrated operation planning method in HVAC processes. It offers better energy conservation, comfort and indoor air quality than other methods being currently used. ISOP consists of two levels of frames. The first level classifies HVAC systems by qualitatively reasoning the system structure information, and activates the subframe. In the second level, 16 frames that correspond to the HVAC system structure, accomplish indoor comfort setting, supply air parameter estimations, air enthalpy, and misture evaluation, and then recommend optimal operation conditions. An integrated distributed intelligent system framework is introduced to integrate qualitative reasoning and quantitative computation.