## 1 Introduction
It is based on a deterministic heuristic algorithm to find the approximate substation service areas for each substation and an expert selection strategy that increases the convergence chance to a globally optimal solution. The effects of unreliability within network feeders and substations are investigated on the obtained layouts. The developed method is applied to four benchmark test systems and an actual large-scale distribution system with about 140,000 customers. Paper [17] proposes an innovative approach based on analyzing a raster map in GIS to perform substation expansion planning for a very large-scale real network. This approach provides an irregular planning mini region to decompose the planning area into irregular mini regions to tackle large-scale real network expansion planning. Meanwhile, the article develops a suitable model regarding the concept of a system of systems to bring about collaborative interactions between mini regions and preserve the integrity of the distribution network. Simulation is performed for a very large-scale sub-transmission system of Mashhad, consisting of 1,359,410 consumers spread in an area of 11,450 km\({}^{2}\), to demonstrate the efficiency of the proposed methodology. In [18], a multistage multiobjective substation siting and sizing optimization model is established, considering various constraints such as load flow constraints, maximum capacity constraints, and power supply radius constraints. The paper focused on an improved multiobjective genetic algorithm, introduced a two-stage operator to repair infeasible solutions, and designed a tournament selection operator based on crowding distance and roulette to prevent early evolution. Lastly, the authors in [19] present an improved methodology to solve the substation siting and sizing problem based on geographic information and supervised learning. The proposed approach can optimize the locations, capacities, and power supply ranges of substations with minimum invest ment. The capital cost of land adds complexity and difficulty to the substation placement problem, especially for highly developed urban areas. The state-of-the-art parallel computing techniques have been employed so that co-optimization for substations of multiple voltage levels can be directly conducted in a computational efficient way. Case studies are presented to demonstrate the effectiveness of the proposed approach. Although several authors have proposed viable methods, GIS features and applications on real urban DNs require deeper investigation. Thus, this paper aims to provide an effective tool for PS optimal siting and timing to expand existing distribution networks. The proposed approach uses a geographic information system for capturing, elaborating, and displaying spatial input data and a PSO algorithm to locate and timing the new primary substations in combination with a Voronoi diagram-based approach to find the primary substation service areas and loading. GIS data are used to identify potential PS locations considering the multitude of constraints that characterize urban areas. PSO and Voronoi diagram algorithms are the optimization framework that guarantees to serve every customer from the nearest PS to ensure that the distribution delivery distance is as short as possible, reducing feeder cost, electric losses costs, and service interruption exposure. Thanks to [PERSON], the approach has been tested on the distribution network of Milan and Rozzano, progressively increasing the number of new primary substations from 1 to 12, looking for a sensitivity analysis. The rest of the paper is organized as follows: In Section 2, the technical background and the problem formulation are reported. The basic concept of PS siting is recapped, and the main features of the proposed approach are presented. Section 3 introduces the proposed GIS-based approach, detailing input data preparation, PS optimal siting, and timing method. Simulation results are reported in Section 4, while conclusions and future works are given in Section 5.