摘要
为了有效解决金属氧化物避雷器(MOA)在线监测难、监测误差较大等问题,通过引入群智能算法中的花朵授粉算法(Flower Pollination Algorithm,FPA),利用花朵授粉算法具有良好的寻优效果来达到需要监测的效果,降低人工监测的失误率,提高监测效率。根据系统运行时的实际电压和泄露电流进行在线的实时监测,并根据这两个参数对MOA等效模型中的参数进行求解,得到能够正常反映系统工况的监测数值。同时,利用MATLAB仿真软件,对电网中的谐波电压和频率进行实时仿真,观测此算法的引入是否能提高监测的准确性,通过计算得到,具有寻优能力的FPA算法,能够将标准差趋近于真实的泄露电流,并且能够有效降低相关系数的最大误差,可得;该算法对此模型中的谐波电压和频率影响较小,同时,具有降低监测误差的能力。
In order to effectively solve the problems of difficult online monitoring and large monitoring errors of metal oxide arresters(MOA),the Flower Pollination Algorithm(FPA)is introduced into the swarm intelligence algorithm,and the flower pollination algorithm has a good optimization performance.To achieve the effect that needs to be monitored,reduce the error rate of manual monitoring,and improve the monitoring efficiency.Online real-time monitoring is carried out according to the actual voltage and leakage current when the system is running,and the parameters in the MOA equivalent model are solved according to these two parameters,and the monitoring values that can normally reflect the system operating conditions are obtained.At the same time,the MATLAB simulation software is used to simulate the harmonic voltage and frequency in the power grid in real time to observe whether the introduction of this algorithm can improve the monitoring accuracy.Through the calculation,the FPA algorithm with the ability to seek optimization can make the standard deviation trend.It is close to the real leakage current and can effectively reduce the maximum error of the correlation coefficient.The algorithm has little influence on the harmonic voltage and frequency in this model,and at the same time,it has the ability to reduce the monitoring error.
作者
朱雪松
张德屯
冯海斌
关洪亮
徐光维
ZHU Xue-song;ZHANG De-tun;FENG Hai-bin;GUAN Hong-liang;XU Guang-wei(Huaneng Hainan Power Inc,Haikou 570100,China)
出处
《电气开关》
2023年第2期50-53,共4页
Electric Switchgear
关键词
金属氧化物避雷器
花朵授粉算法
在线监测
频率
谐波电压
metal oxide arrester
flower pollination algorithm
online monitoring
frequency
harmonic voltage
