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Central air-conditioning system parallel chiller system energy consumption is very large, if improper operation,energy consumption will be greatly increased.An improved whale population optimization algorithm is proposed to solve the continuous nonlinear optimization problem of OCL problem.Firstly, in order to make the search space of the subsequent iteration more accurate, the chaotic mapping is used to initialize the population,so that the initial solutions evenly spread across the solution space. Secondly, the variation index is introduced to improve the convergence factor and balance the relationship between local exploration and global exploration.After that, sine and cosine are introduced to make the algorithm converge to the global optimal solution,which prevents premature convergence of the algorithm and improves the convergence accuracy of the algorithm.Finally, the performance of IWOA algorithm is evaluated by two typical cases and compared with other optimization algorithms applied to OCL problems.The results show that IWOA algorithm is an effective method to solve OCL problem.In addition, the comparison of algorithm performance shows that IWOA algorithm provides a better solution than other optimization methods applied to OCL problems in terms of convergence speed and power consumption.