Energy management in buildings is an important issue due to its great impact in energy consumption. Significant energy savings can be achieved by optimal operation of multi-chiller systems. This paper presents a modified co-evolutionary particle swarm optimization (MCPSO) algorithm to solve the optimal chiller loading problem. The proposed approach is based on particle swarm optimization (PSO) algorithm which employing the notion of co-evolution to adapt penalty factors. The performance of the proposed method is evaluated on two test systems. The results show that the proposed method can obtain better solution compared with other methods found in recent literature.
