【摘要】 电力系统动态经济调度（DED）是一种复杂的多目标优化问题，旨在使发电机组的总燃料成本和污染排放最小化。然而，由于约束条件的复杂性，一般的数学方法难以解决这个问题。因此，本文采用了旗鱼优化算法（SFO）来解决考虑风电情况下的动态经济调度问题。为了验证SFO算法的性能，本文使用了5台火电机组的测试系统，并在MATLAB软件中对模型进行了仿真和测试。实验结果表明，SFO算法能够有效降低电力系统的燃料成本和污染排放，从而提高电力行业的经济效益。更多还原

【Abstract】 Dynamic economic dispatch( DED) of power system is a complex multi-objective optimization problem that aims to minimize the total fuel cost and pollution emissions of generating units. However, due to the complexity of the constraints, general mathematical methods are difficult to solve this problem. Therefore,this paper adopts the swordfish optimization algorithm(SFO) to solve the dynamic economic dispatch problem considering wind power. In order to verify the performance of the SFO algorithm, this article uses the test system of 5 thermal power units, and simulates and tests the model in MATLAB software. Experimental results show that the SFO algorithm can effectively reduce the fuel cost and pollution emissions of the power system,thereby improving the economic benefits of the power industry.更多还原