Optimization of Power Flow using GA Fuzzy Approach

Abstract

: The optimal power flow (OPF) issue is a critical optimization job in the operation and planning of power systems. It entails establishing the best settings of control variables to minimize generating costs while meeting operational restrictions. Traditional optimization techniques often struggle to handle the complexities and uncertainties inherent in power systems. This paper introduces fuzzy systems' concepts and their integration with genetic algorithms. It then delves into the many possibilities for power system optimization problems. The first section introduces the fundamental ideas of fuzzy, while the second section explores its structure and components. The third section explores the genetic algorithm's synergism with the fuzzy technique. The suggested technique was evaluated on an upgraded IEEE 30-bus system, with an optimal solution indicating fuel cost reduction under various linear and non-linear constraints. The suggested methodology's results were compared to all those mentioned in the literature. The outcomes of the offered methodologies are encouraging, demonstrating the efficacy and resilience of the proposed procedures. The synergism of the fuzzy system with the genetic algorithm offers several advantages, including flexibility in handling uncertainties, adaptability to complex systems, and the potential for discovering innovative solutions. However, it is important to carefully design the fuzzy system's rule base and appropriately set the genetic algorithm's parameters for optimal performance.