基于粒子群算法的变电站工频电场优化

发布时间：2018-10-10 20:46

【摘要】：为降低变电站工频电场曝露水平,避免工作人员长期曝露其中可能造成的健康威胁,通过优化电站设备布局来降低一次设备周围近地面空间电场强度。建立220 k V户外配电设备3维几何模型,采用软件仿真计算出220 k V户外配电区电场分布,并将电场强度高于限值的设备区作为待优化区域。提出适用于变电站电场优化问题的粒子群优化算法的适应度函数和限制条件。以降低设备区外部电场分布作为优化目标,对其进行整体优化计算,在此基础上,以降低设备区内部高场强分布作为优化目标对相关设备位置进行微调。最后将计算所得最优电场分布与原电场分布进行对比,整体优化后的适应度函数值减小了83.4%,局部优化后适应度函数值再次减小了29.1%。优化结果表明,利用粒子群算法对设备排布重新优化,可以在不增加建设成本的前提下降低目前变电站工频电场曝露水平。
[Abstract]:In order to reduce the exposure level of power frequency electric field in substation and avoid the possible health threat caused by long-term exposure of the workers, the electric field intensity near the ground around the primary equipment is reduced by optimizing the layout of the power plant equipment. The 3D geometric model of 220kV outdoor distribution equipment is established. The distribution of electric field in 220kV outdoor distribution area is calculated by software simulation, and the area where the electric field intensity is higher than the limit value is regarded as the optimal area. The fitness function and limiting conditions of particle swarm optimization (PSO) algorithm for substation electric field optimization are presented. In order to reduce the external electric field distribution of the equipment area as the optimization objective, the overall optimization calculation is carried out. On this basis, the location of the related equipment is fine-tuned by reducing the high field intensity distribution in the equipment area as the optimization target. Finally, by comparing the calculated optimal electric field distribution with the original electric field distribution, the fitness function value of the whole optimization is reduced by 83.4and the fitness function value after local optimization is reduced again by 29.11um. The optimization results show that the PSO algorithm can reduce the exposure level of power frequency electric field in substation without increasing the construction cost.
【作者单位】：同济大学电子与信息工程学院;宁波耀华电气科技有限责任公司;
【基金】：国家自然科学基金(51577135)~~
【分类号】：TM63

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