## 1 Introduction
### Literature Review  
Numerous studies have been carried out in the literature on the accuracy of the state estimation process in EDNs, indicating that the sampling rate and the measuring device's accuracy are some of the factors that can affect the results. The DNOs can use devices such as the RTUs or micro-phasor measurement units (\(\upmu\)PMUs) in the EDNs to improve their protection and monitoring capabilities. Regarding the \(\upmu\)PMUs, their placement inside the EDNs can be more challenging than the RTUs integrated into the SCADA system. This situation can appear due to the different factors that affect the EDN's operation, which are associated with the high number of lateral branches, the EDN's structure, and the unknown voltage transformer tap ratio. Besides these, other factors, such as the need for phase observability and the frequent topology changes due to the reconfiguration process, are also considered to ensure the EDN is stable [9]. Thus, through RTUs integrated into the SCADA system implemented at the MV/LV EDSs level, DSOs can ensure the network's observability with affordable investments. The advantages of RTUs-based measurements include utilising current technical infrastructure and the new generation of smart SCADA technology integrating artificial intelligence, big data analytics, and the Internet of Things [10]. This new technology allows for better control and optimisation, making it a powerful tool for DNOs. Determination of the optimal number of electric distribution substations (EDSs) with the RTUs integrated into the SCADA system to perform on-site measurements used in the state estimation process of the EDNs represents a challenge both from a technical and economic point of view for DNOs. It involves developing a robust framework incorporating algorithms to model the EDN's conditions accurately. Most placement approaches proposed in recent years are based on metaheuristic methods. Metaheuristic methods are versatile and can be modified to meet specific requirements. These advantages make them ideal for addressing optimisation problems, such as measuring device placement in EDNs. [PERSON] et al. [11] proposed the binary dragonfly algorithm in the optimal measurement device placement to estimate the state of an EDN. However, the algorithm has been tested only in a radial EDN without considering a looped topology. [PERSON] et al. [12] presented a greedy approach-based placement scheme that aims to find the optimal number of devices while satisfying the grid observability constraints. The state estimation results specify the limits, which are defined as the voltage magnitudes and currents at the nodes and lines. The proposed placement approach has been tested in an MV EDN with few nodes (only 10 nodes). [PERSON] et al. [13] proposed a derivative-free algorithm (similar to a genetic algorithm) to identify the optimal locations where the measurements are performed to state estimation in complex EDNs. The results indicated a high accuracy of the proposed approach, but the testing in the looped EDNs is missing. [PERSON] et al. [14] used a method that considers the observability of various monitoring devices and the importance of the EDNs' nodes in placing on-site measurements at essential nodes. They thought the devices' observability impact on the placement scheme reduced the number of monitoring devices while improving the system's observation performance. However, the proposed method did not consider the implications of the observation redundancy of each node. Due to the limited measurement sources, the absence of state estimation technology has hindered its application in the EDNs. Even if optimal on-site measurements provided by the RTUs integrated into the EDSs are available, an EDN cannot be fully observable without information from all EDSs. This issue can be addressed by adding measurements in the EDSs without integration into the SCADA system and employing a reliable pseudo-metering model, which can enhance the feasibility of state estimation in the EDNs.