With the increasing environmental concerns, the world is moving towards rapid decarbonization, and to meet the growing energy demand, more renewable energy sources like solar, Wind are getting added to the existing Distribution grid. The addition of new loads like Electric vehicles (EV), Heat pumps, etc. is putting additional pressure on the grid leading to some technical problems. Due to this, it is important to have real-time monitoring of the system by the Distribution System Operators(DSO)s which can be obtained by performing the State Estimation. The Distribution System State Estimation along with the state estimator has been discussed in the literature.

However, the accuracy of the state estimation is highly affected by the absence of real measurements from the meter and the presence of high-variance pseudo measurements. But due to the cost factor, it is practically not possible to install meters at every node. To reduce the state estimation error, a new meter placement strategy has been proposed in this project with the help of open-source software called Power Grid Model, devolved by the Dutch DSO Alliander for performing steady state analysis of the network.

The work presented in this project includes a sensitivity analysis of the proposed meter placement algorithm which is applied to a test MV distribution network in the Netherlands for the different sample sizes of the load profile as well as the standard deviation of the pseudo measurements. The application of the meter placement algorithm results in a subsequent reduction of the state estimation error. To find a suitable number of meters that can be placed in the network, three-meter placement criteria have been proposed and applied to the test network. The results show the effectiveness of the proposed meter placement algorithm for the determination of a suitable path as well as the number of meters that can be placed in the distribution network. This is important for the grid operators as it will help them to make decisions for the proper maintenance and operation of the grid.