Load Profile Estimation in Distribution Network using Optimal Alocation of RTUs

the largest part of an electrical grid is distribution system, which is directly in contact with people. Therefore, the importance of automation in this section is quite evident. In addition, the number of distribution substations is very high and implementation of automation devices in all distribution substations is not economically affordable because it requires a large amount of investment. Thus, it is necessary to have a powerful state estimation method to have information about the distribution network based on the limited measurements done in this system. In this paper, a new artificial intelligence (AI) based method is presented to load profile estimation in distribution network. By using the proposed method, the number of the Remote Terminal Units (RTU) needed for state estimation is determined such that the load profile can be estimated in all of the buses.