Generalization of redundancy analysis in electrical power system measurement

• Grant number: 07/01067-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2007
• End date: December 31, 2007
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Joao Bosco Augusto London Junior
• Grantee: Ricardo Cartolano
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

The purpose of the process of power system state estimation is to determine, in real-time, the power system state variables, that is, the complex voltage in the buses of the system, by processing a redundant collection of analog measurements usually composed by: active and reactive power measurements and voltage magnitude measurements. A high level of measurement redundancy is essential for a reliable state estimation of power system. Redundancy is important, not only to guarantee observability, but also to guarantee the absence of both critical measurements and critical sets. Since it is not possible either to detect gross errors (GEs) on critical measurements, or to identify the presence of GEs on measurements pertaining to critical sets, methods for identification and updating of measurement redundancy level have been developed in the last decades. However, these methods were developed basing on the Ptheta model (active power measurements - voltage angles), and, to be used to the QV model (reactive power and voltage magnitude measurements - voltage magnitudes) it is necessary some adaptations for the QV model. The problem is that in some situations those adaptations do not work well. This project proposes a generalization of the methodology developed for the identification of the local measurement redundancy level, through the analysis of the structure of so called HDelta matrix. The objective is to turn that methodology able to analyze the local redundancy level of the measurements associated with the Ptheta and QV model coupled together and/or decoupled them, without considering those adaptations mentioned above (related to the QV model).