No abstract

This paper presents a variable neighborhood search (VNS) optimization algorithm for the design of the parameters of supplementary damping controllers: power system stabilizers (PSS) and the interline power flow controller-power oscillation damping (IPFC-POD) set. The objective is to insert damping to local and inter-area oscillation modes in multimachine power systems. The electric power system dynamics is represented by the current sensitivity model. Simulations were carried out using three systems: a test system known as Two-Area Symmetrical and two real systems, the New England and the Reduced Southern Brazilian. The VNS method was compared with a multi-start algorithm in terms of performance, showing better convergence rates. The proposal was also able to obtain solutions with high damping levels, that showed to be robust when changes on the operating point of the power system were considered. Finally, it has been verified that the PSS controllers were effective for damping the local mode oscillations, while the IPFC-POD set operated mainly damping the inter-area modes.

This paper presents a technique based on the novel bat algorithm (NBA) for the design of the parameters of power system stabilizers and the generalized Unified power flow controllerpower oscillation damping in a multimachine power system. The objective is to ensure minimal damping rates to low-frequency electromechanical oscillation modes. Simulations were carried out on the New England system to compare the performance of the NBA with three other techniques: particle swarm optimization, bacterial foraging optimization oriented by particle swarm optimization, and the bat algorithm. For the cases analyzed in this paper, the NBA produced results superior to other techniques. Moreover, the proposed methodology was able to obtain solutions with high damping levels, which showed to be robust when a wide range of loading conditions of the power system were considered.

No abstract

This paper presents a Specialized Chu-Beasley's Genetic Algorithm (SCBGA) to perform coordinated tuning of the parameters of proportional-integral and supplementary damping controllers (power system stabilizers and interline power flow controller-power oscillation damping) in multi-machine electric power systems. The objective is to insert additional damping to low frequency electromechanical oscillations. The current sensitivity model was used to represent the system, therefore all of its devices and components were modeled by current injection. A novel current injection model for the interline power flow controller is presented and a static analysis is considered to validate it. The New England test system-consisting of 10 generators, 39 buses, and 46 transmission lines, divided into two areas with both local and inter-area oscillation modes-was used for the simulations. The SCBGA was compared to other five algorithms: a Random Search, a Local Search, a Simulated Annealing, a Genetic Algorithm, and a Particle Swarm Optimization method, in terms of performance for the tuning of the parameters of the controllers. The results demonstrated that the SCBGA was more efficient than these other techniques. In addition, the obtained solutions proved to be robust when variation of the loads was considered.