An Enhanced Tuna Swarm Algorithm for Optimizing FACTS and Wind Turbine Allocation in Power Systems

Abstract

The significance of FACTS devices has been increasing as they have the ability to donate compensation for power systems, making a significant impact on power system stability and power transfer issues. However, to optimize the performance of these devices, it is important to carefully select their sizes and locations. This article aims to determine the optimal size and location of several FACTS devices to achieve two objectives: minimizing fuel costs and minimizing power losses. These objectives are solved one by one, then combined into a multi-objective function to minimize gross cost. An Enhanced Tuna Swarm Optimization is proposed to improve the performance of the original version of Tuna Swarm Optimization. The traditional Tuna swarm optimization is improved relying on “high and low-velocity ratios” included in the Marine Predator Algorithm. The main advantage of this approach is to avoid the risk of the optimal value being trapped in local minima. The IEEE 30-bus standard system is used as a case study, with SVC, TCSC, and TCPS installed as FACTS devices, and two wind turbines as renewable resources penetration. Different optimization algorithms are used, and a comparison is made to prove the superiority of the proposed algorithm compared to the other tested algorithms.