District cooling plant has been widely used in comfort cooling service (for airport, university, shopping mall, etc.) and industry process cooling service. However, current district cooling plants are becoming more complex with hybrid cooling equipment such as Steam Absorption Chiller, Electric Chiller, Thermal Energy Storage, etc., it's challenging to implement energy efficient cooling operation with high cooling performance and low energy consumption. Conventional optimization uses cost objective function to calculate energy consumption with operation scheduling variables as input. Through searching variables' space, the variable set with minimum energy cost is selected as optimal operation solution. However, this method is not valid when correlation between power consumption and scheduling variable is weak. The present paper enhances operation scheduling optimization by integrating RCA (Root Cause Analysis) method to identify the occasion when the required correlation is strong and optimization objective function can be applied. Also, the proposed method can integrate with empirical performance knowledge to solve local optimization problem. The experiments at district cooling plant of UTP (Universiti Teknologi PETRONAS) shows new operation scheduling optimization can save power by 50 averagely. © 2017 IEEE.