A new approach for optimal chiller loading using an improved imperialist competitive algorithm

[Display omitted] •Apply the differential mutation idea that was proposed by differential evolution to ICA.•The ICA-DE allows colonies to learn not only from their corresponding imperialists but also from other colonies.•The novel ICA-DE method for distributing the partial load rate (PLR) of chillers.•The established model was experimentally verified in an actual multi-chiller system in a building. A new optimization algorithm based on an improved imperialist competitive algorithm (ICA-DE) is proposed to reduce the energy consumption of a multi-chiller system. The assimilation process is very important in ICA. Colonies of empires move randomly toward imperialists during the assimilation process in ICA, which decreases population diversity and can lead to premature convergence. Therefore, to create more new locations for colonies and increase population diversity, the idea of differential mutation proposed by differential evolution (DE) was applied to ICA. The novel ICA-DE method was used to distribute the partial load rate (PLR) of chillers to solve the optimal chiller loading (OCL) problem, with the goal of minimizing the energy consumption of multiple chillers. The established model was experimentally verified in an actual multi-chiller system in a building, and the results showed that the ICA-DE method can achieve good results. Finally, the ICA-DE method was compared with GA, DE, PSO, DCSA and ICA in two different test systems. The results show that the ICA-DE method has superior performance.