Fast methods for selection of preventive and corrective controls in electric power systems considering load uncertainties

• Grant number: 18/24815-7
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: March 01, 2019
• End date: March 31, 2022
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Luís Fernando Costa Alberto
• Grantee: Lucas Sales Neves
• Host Institution: Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• Associated research grant: 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment, AP.TEM

Abstract

The increase in demand of electrical energy of the current Electric Power Systems (EPS) forces them to operate closer to their limits. Therefore, it is becoming increasingly necessary the research and implementation of safety analysis tools to ensure the stable operation of these systems in the face of load variations. In addition, in the current EPSs, there is a penetration increase of intermittent sources of electricity generation associated with alternative sources. Since unforeseen variations in the generation of these intermittent sources may lead the EPS to instability, these uncertainties need to be considered in stability studies. In this context, a difficulty currently encountered in voltage stability analysis of EPSs concerns the feasibility of applying computational tools for real-time safety analysis in large systems. The computational cost of these tools intensifies when the safety analysis seeks to determine ways to restore the stability of the system by means of corrective and preventive controls. Clearly, the development of fast tools for stability assessment and control selection is very important, since a possible loss of stability must be quickly repaired. Among these problems, this research project aims at the development and implementation of a new method that calculates the load margin in EPSs and, if necessary, rank and select preventive and corrective controls that guarantee voltage stability. While the method must be robust by incorporating both the loading uncertainties present in the current EPSs and the operational limits of the system, the method must be fast for real-time application. This method will be based on the Point of Collapse method, on optimality concepts of mathematical optimization problems and on load margin sensitivity analyses in relation to the available EPS controls. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

NEVES, LUCAS SALES; COSTA ALBERTO, LUIS FERNANDO; CHIANG, HSIAO-DONG. Smooth Power Flow Model for Unified Voltage Stability Assessment: Theory and Computation. IEEE Transactions on Power Systems, v. 37, n. 6, p. 11-pg., 2022-11-01. (14/50851-0, 18/20104-9, 18/24815-7)

NEVES, LUCAS SALES; COSTA ALBERTO, LUIS FERNANDO; CHIANG, HSIAO-DONG. Fast contingency screening for voltage stability analysis considering both SNBs and SIBs. Electric Power Systems Research, v. 213, p. 6-pg., 2022-08-13. (14/50851-0, 18/20104-9, 18/24815-7)

NEVES, LUCAS SALES; COSTA ALBERTO, LUIS FERNANDO; CHIANG, HSIAO-DONG. A fast method for detecting limit-induced bifurcation in electric power systems. Electric Power Systems Research, v. 180, MAR 2020. (14/50851-0, 17/22397-0, 18/24815-7)

NEVES, LUCAS SALES; COSTA ALBERTO, LUIS FERNANDO. On The Computation of The Locally Closest Bifurcation Point Considering Loading Uncertainties and Reactive Power Limits. IEEE Transactions on Power Systems, v. 35, n. 5, p. 3885-3894, SEPT 2020. (18/24815-7, 17/22397-0, 14/50851-0, 18/20104-9)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

NEVES, Lucas Sales. Fast methods for voltage stability analysis and control selection considering parameter uncertainties. 2022. Doctoral Thesis - Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD) São Carlos.