免疫原理的智能配电网自愈系统关键技术分析

Analysis of key technologies of self-healing system of intelligent distribution network based on immune principle

传统的智能配电网自愈系统在故障数据采集的过程中会出现偏差,针对这个问题提出免疫原理的智能配电网自愈系统关键技术。根据自愈环网中对开关运动控制操作次数的限制,确定负荷的加权系数,完成目标函数模型的建立,利用随机树算法产生抗体,进行抗原的动态操作来引入免疫原理算法,最后通过对数据传感器的电压进行控制来实现数据传感器的优化,完成了对免疫原理的智能配电网自愈系统关键技术的分析。为验证提出的关键技术的有效性,在仿真环境下设计了对比实验。根据实验结果可知,利用提出的技术平均在每100个故障能采集到99.6个,比传统技术高出11.2个,验证了免疫原理的智能配电网自愈系统关键技术的有效性。

The traditional intelligent distribution network self-healing system will have deviations in the process of fault data collection.Aiming at this problem,the key technology of the intelligent distribution network self-healing system based on the immune principle is proposed.According to the limit of the number of switching motion control operations in the self-healing ring network,the weighting coefficient of the load is determined,and the establishment of the objective function model is completed.Using a random tree algorithm to generate antibodies,dynamic operation of the antigen is used to introduce the immune principle algorithm.The voltage of the sensor is controlled to optimize the data sensor,and the analysis of the key technologies of the intelligent distribution network self-healing system based on the immune principle is completed.To verify the effectiveness of the proposed key technologies,a comparative experiment was designed in a simulation environment.According to the experimental results,it can be known that,using the proposed technology,an average of 99.6 faults can be collected per 100 faults,which is 11.2 higher than the traditional technique.