Georeferenced rural distribution network model considering scalable growth of users in rural areas. Issue 1 (January 2023)

• Record Type: Journal Article
• Authors: García, Juan; Inga, Esteban
• Is Part Of: Heliyon. Volume 9:Issue 1(2023)
• Publication Date: 2023-01
• Subjects: Planning -- Optimization -- Heuristics -- Resources -- Underground electrical distribution networks; Research -- Periodicals; Medical sciences -- Periodicals; Natural history -- Periodicals; Social sciences -- Periodicals; Earth sciences -- Periodicals; Physical sciences -- Periodicals; 507.2
• DOI: 10.1016/j.heliyon.2022.e12724
• Languages: English
• ISSNs: 2405-8440

Abstract

Abstract: This paper presents a georeferenced optimal planning model of a rural distribution network for deploying an underground network considering a real scenario for increasing electrification in this area. A model is presented based on a heuristic process that minimizes the resources required to route the grid for a defined time horizon. Then, the model is scalable according to the population density, the established and georeferenced zone, and the specified period; that is, it adjusts to any of these variables. Additionally, the modeling is presented in CYME software, considering a series of technical criteria to provide the actual scenario with a verifiable planning model of an underground network. Therefore, the voltage drop and level of overload in transformers and feeders are considered to deliver an optimum power quality to the end-user. These results will be tabulated and presented as an alternative to different planning and design models that an electric distribution company may have to minimize the resources used in an underground deployment. Highlights: The optimal planning model for rural distribution networks is a valuable tool before an electrical grid's design and expansion phases, allowing the increase of electrification in a given scenario. According to the proposed heuristic model, the minimization of resources in an electrical distribution system allows the partial optimization of a scenario. The use and application of graph theory and MST in resource minimization for rural distribution networks optimize the resources considered in any network topology. The proposed model is scalable according to a time horizon; it is scalable according to the demographic expansion of the proposed scenario. It allows for the planning and design of a network, starting from a local standard or an international standard, i.e., the proposed model is scalable at several levels.