Penalty function and particle swarm optimization for solving the optimal power flow problem with discrete control variables

• Grant number: 17/14782-1
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: November 01, 2017
• End date: April 30, 2019
• Field of knowledge: Engineering - Electrical Engineering - Power Systems
• Principal Investigator: Edilaine Martins Soler
• Grantee: Gabriel Uri Brito Davansso
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

The purpose of an Optimal Power Flow problem is to determine the state of a power transmission system that optimizes a specific performance of this system and satisfies its physical and operational constraints. The Optimal Power Flow problem can be mathematically modeled as a nonlinear programming problem with discrete and continuous variables. Due to the difficulty in solving this problem because of the discrete variables, most of the approaches in the literature ignore the discrete nature of these variables and consider all the variables of the Optimal Power Flow problem as continuous variables. These formulations are not realistic because some controls can be only adjusted by discrete steps. This research project aims to develop and apply to the Optimal Power Flow problem with discrete variables a solution approach that uses penalty functions to handle the discrete variables of the problem, thus obtaining a continuous problem that is equivalent to the original, and this penalized problem will be solved by the particle swarm optimization method. Numerical tests with the IEEE test systems will be performed to validate the developed approach. (AU)