Adaptive PSO Based Tuning of PID- Fuzzy and SVC-PI Controllers for Dynamic Stability Enhancement: A Comparative Analysis

Abstract

The power system is a dynamic system. Satisfactory damping of power oscillations is an important concern when dealing with the rotor angle stability. To improve the damping of oscillations in power systems, supplementary control laws can be applied to existing devices. In this paper, a PID fuzzy controller structure and optimal PI controller of a static Var compensator (SVC) are presented and implemented on single machine infinite bus system for improving the oscillations damping. The parameters of both the PID fuzzy controller and SVC-PI controllers are tuned by the adaptive particle swarm optimization (APSO).Index Terms-Power system stabilizer, fuzzy logic control, adaptive PSO, PID controller, PI controller, static var compensator. X. BIOGRAPHIESM. Sridhar is currently pursuing PhD in the department of electrical engineering, AU College of engineering, Andhra University, Visakhapatnam-530003, AP, India. His research interests include power system dynamics and stability, voltage stability and FACTS applications.K. Vaisakh is currently working as a professor in the department of electrical engineering, AU College of engineering, Andhra University, Visakhapatnam-530003, AP, India.His research interests include power system operation and control, power system stability, and soft computing techniques.K. S. Linga Murthy is currently working as a professor in the department of electrical engineering, AU college of engineering, Andhra University, Visakhapatnam-530003,AP,India. His research interests include economic power dispatch, power system optimal operation and control.

Self-scheduling approach for large consumers in competitive electricity markets based on a probabilistic fuzzy system

“…Particle swarm optimisation algorithms, which are population-based evolutionary search techniques, have been widely used for fuzzy membership function tuning [17 -19]. Furthermore, PSO algorithms are fast and easy to code and are suitable for solving high-dimensional problems [17]. In PSO, particles flow in a multi-dimensional search space and the position of each particle is tuned based on the experiences gained by him and his neighbours.…”

Optimal Coordination of Multiple ESS-based Stabilizers and PSS in Multi-machine Power System for Damping Improvement

“…The results of eigenvalue after optimization in 4-machine power system are shown in Table 2. In order to validate the efficiency of IPSO algorithm, the comparison between the IPSO and the adaptive particle swarm optimization (APSO) algorithm (Sridhar et al, 2009) is shown in Fig. 4.…”

Control of SVC based on the sliding mode control method

“…In order to correspond with these demands, controllers with static var compensators (SVCs) are used. Some of these controllers are neuro-fuzzy SVCs [1,2], fuzzy-proportional-integral-derivative (PID) controllers [3,4], nonlinear and H ∞ controls [5,6], adaptive controls [7] and intelligent controllers [8], fuzzy logic [9,10] optimal predictive controllers [11], and nonlinear and nonlinear robust controllers [12,13].…”