Multi-objective Optimal Power Flow and Emission Index Based Firefly Algorithm

Abstract

The economic operation of electric energy generating systems is one of predominant problems in energy systems. In this work one evolutionary optimization method, based on the meta-inference behavior called the Firefly Algorithm (FFA) is applied to solve such as the multipurpose optimum power flow (OPF) and emission index (EI) problems. Our main goal is to improve the objective function necessary to achieve the best balance between production and its energy consumption, which is presented as a non-linear function, taking into account some constraints of equality and inequality. The goal is to reduce the total cost of generations, active losses, and emission index.
The FFA approach was examined and tested on a standard IEEE-30 bus system. The validations of obtained results were compared with some well-known and recently published references. The efficiency and credibility of the proposed method has been proven by the obtained results.