基于多目标粒子群算法的高维多目标无功优化

发布时间：2019-06-11 05:23

【摘要】：提出一种高维多目标电力系统无功优化模型。相比于传统的电力系统无功优化模型,该模型能够在无功优化中同时兼顾系统的有功损耗、电压水平、静态电压稳定性以及供电能力。针对已有的求解多目标无功优化模型的算法应用于求解所提模型时存在的局限性,进一步引入一种基于帕雷托熵的高维多目标粒子群优化算法并加以改进,使得该算法能够有效求解高维多目标优化问题。最后,利用IEEE-39节点系统验证了所提模型和求解算法的正确性和有效性。仿真结果表明,在传统的多目标无功优化模型中引入系统供电能力,能够在不恶化其他目标函数优化效果的情况下,使系统的供电能力得到提高。
[Abstract]:A reactive power optimization model for high dimensional multi-objective power system is proposed. Compared with the traditional reactive power optimization model, this model can take into account the active power loss, voltage level, static voltage stability and power supply capacity at the same time in reactive power optimization. In view of the limitations of the existing algorithms for solving the multi-objective reactive power optimization model, a high-dimensional multi-objective particle swarm optimization algorithm based on Pareto entropy is further introduced and improved. So that the algorithm can effectively solve the high-dimensional multi-objective optimization problem. Finally, the correctness and effectiveness of the proposed model and algorithm are verified by IEEE-39 node system. The simulation results show that the power supply capacity of the system can be improved without deteriorating the optimization effect of other objective functions by introducing the power supply capacity into the traditional multi-objective reactive power optimization model.
【作者单位】：华北电力大学新能源电力系统国家重点实验室;
【基金】：国家自然科学基金项目(51677069)~~
【分类号】：TM714.3;TP18

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