Resolution of optimal power flow problem with discrete control variables

Author(s)

Edilaine Martins Soler

• Document type: Doctoral Thesis
• Press: São Carlos.
• Institution: Universidade de São Paulo (USP). Escola de Engenharia de São Carlos (EESC/SBD)
• Defense date: 2011-03-01

Examining board members

Eduardo Nobuhiro Asada; Edméa Cássia Baptista; José Roberto Sanches Mantovani; Aurelio Ribeiro Leite de Oliveira; José Carlos de Melo Vieira Júnior

• Advisor: Geraldo Roberto Martins da Costa

Abstract

The aim of solving the Optimal Power Flow problem is to determine the state of an electric power transmission system that optimizes a given system performance, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. In most techniques existing in the literature to solve the Optimal Power Flow problems, the discrete controls are modeled as continuous variables. These formulations are unrealistic, as some controls can be set only to values taken from a given set of discrete values. This study proposes a method for handling the discrete variables of the Optimal Power Flow problem. A function, which penalizes the objective function when discrete variables assume non-discrete values, is presented. By including this penalty function into the objective function, a nonlinear programming problem with only continuous variables is obtained and the solution of this problem is equivalent to the solution of the initial problem that contains discrete and continuous variables. The nonlinear programming problem is solved by a Interior-Point Method with filter line-search. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the proposed approach is efficient in the resolution of OPF problems. (AU)

• FAPESP's process: 07/07942-0 - Optimal adjust of continuous and discrete variables in nonlinear programming problems
• Grantee: Edilaine Martins Soler
• Support Opportunities: Scholarships in Brazil - Doctorate