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Methodologies for distribution system State Estimation

Grant number: 14/00293-0
Support Opportunities:Scholarships abroad - Research
Effective date (Start): August 01, 2014
Effective date (End): July 31, 2015
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:Madson Cortes de Almeida
Grantee:Madson Cortes de Almeida
Host Investigator: Luis Fernando Ochoa Pizzali
Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Research place: University of Manchester, England  
Associated research grant:10/01690-2 - Technological development for protection, analysis, supervision and automation of electrical power systems of the future, AP.TEM


Despite the consolidation reached by state estimation approaches adopted in transmission systems, such advances are not observed in distribution networks. This is mostly due to the low degree of automation, lack of measurement and communication usually employed in distribution systems. Furthermore, particular characteristics of distribution systems represent barriers to the successful employment of transmission state estimators in distribution grids. On the other hand, residential, commercial and industrial consumers have become increasingly sensitive to variations in power quality over the past few decades. In addition to it, the unbundling of the electricity sector resulted in the creation of stricter regulatory standards. Additionally, recent advances in Automatic Meter Reading (AMR) and Advanced Metering Infrastructure (AMI), the advent of Phasor Measurement Units (PMUs) and the great expectation and efforts currently undertaken by regulators, governments and utilities to develop and deploy the Smart Grid initiative tend to modify and intensify the use of state estimators in the Distribution Management Systems. The main objective of this project is the development of new formulations for distribution systems state estimation (DSSE) devoted to distribution systems. For the DSSE implementation, the following additional issues can still be investigated: optimal allocation of smart meters in order to enhance the DSSE, load forecasting methodologies for pseudomeasurement fitting and the development of modern distribution systems applications based in state estimation. (AU)

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