基于改进哈里斯鹰算法的数字孪生变电站监控网络覆盖优化OA

To improve the coverage performance of the digital twin substation monitoring network,a coverage optimization method for the digital twin substation monitoring network based on an improved Harris eagle algorithm is proposed.The objec-tive function for the monitoring network coverage of digital twin substations is to maximize the sum of coverage rate and repeat-ed sampling rate,and the constraints on network coverage are given.In order to improve the solving performance,tent chaotic mapping is introduced to generate the Harris eagle initialization population,and the golden sine algorithm is introduced to re-duce the search space of the Harris eagle algorithm and improve its convergence speed.An improved Harris eagle objective function solving algorithm is proposed.The verification is carried out on the Autodesk 3DS MAX platform.The results show that compared with manual experience,the coverage rate and repeated sampling rate of the proposed method increases by 17.53％and 30.71％respectively.Compared with the comparison method,the coverage rate increases by approximately 10％,and the repeated sampling rate increases by approximately 15％.From this,it can be concluded that the proposed method can sig-nificantly improve the network performance of the digital twin substation monitoring network and achieve coverage optimization of the digital twin substation monitoring network.