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Development of a GIS-based tool for the analysis of future distribution networks

Grant number: 16/20642-5
Support type:Scholarships abroad - Research Internship - Scientific Initiation
Effective date (Start): February 01, 2017
Effective date (End): May 31, 2017
Field of knowledge:Engineering - Electrical Engineering
Principal Investigator:Fernanda Caseño Trindade Arioli
Grantee:Guilherme de Oliveira Custodio
Supervisor abroad: Luis Fernando Ochoa Pizzali
Home Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Local de pesquisa : University of Melbourne, Australia  
Associated to the scholarship:16/11070-8 - Exploration of measurement data from smart meters for the management of power distribution systems, BP.IC

Abstract

Distribution networks are likely to experience in the next decade significant infrastructural changes due to the massive integration of distributed energy resources, plug-in electric vehicles as well as sensors and meters. These changes are going to be accompanied by an increase in the complexity of planning and operational tasks, requiring new paradigms in how Distribution Network Operators (DNOs) will manage future Smart Grids. As distribution networks become more observable and controllable, more sophisticated network analysis tools are required and such tools must be able to integrate the available data in order to allow advanced Smart Grid studies. In this context, this project aims to develop a Geographic Information System (GIS)-based tool for the analysis of future distribution networks, using three main open-source software tools: Python, OpenDSS and QGIS. With this purpose, the candidate will have access to geographic information from real distribution networks, obtained from ongoing industry projects in Australia and Brazil. The GIS-based tool will be beneficial to an extensive range of studies dedicated, for instance, to the following DNO tasks: route optimization (crew dispatch), non-technical loss detection and location, topology database correction, outage management, asset management, integration of distributed energy resources, and plug-in electric vehicles. (AU)