Power system stabilization based on artificial intelligent techniques: a review
Document Type
Conference Item
Publication Date
12-1-2009
Abstract
This paper reviews new approaches in modern research using Artificial Intelligent (AI) techniques to develop power system stabilizer (PSS). These techniques are Artificial Neural Network (ANN), fuzzy logic, hybrid artificial intelligent, expert systems, and optimization techniques base AI such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search (TS) algorithm, etc. Research showed controllers designed based on a conventional control theory, modern and adaptive control theories, suffer from some limitations. However, AI techniques proved to be able to overcome theses limits. Hence, more researchers preferred to utilize these approaches for the power systems. The review efforts geared towards PSS and excitation system stabilizer developed based on AI techniques, which effectively enhance both small signal stability and transient stability and equally provide superior performances. In addition, the dynamic performance of different AI based stabilizers are established and compared with other types of PSSs.
Keywords
Adaptive Control, AI techniques, Artificial intelligent, Artificial Neural Network, Conventional control, Dynamic performance, Excitation system, New approaches, Optimization techniques, Power system stabilization, Power system stabilizers, Power systems, Small signal stability, Tabu search algorithms, Transient stability, Control theory, Electric power systems, Expert systems, Fuzzy logic, Genetic engineering, Neural networks, Particle swarm optimization (PSO), Research, System stability, System theory, Tabu search, Adaptive control systems
Divisions
fac_eng
Event Title
International Conference for Technical Postgraduates, TECHPOS 2009
Event Location
Kuala Lumpur, Malaysia
Event Dates
14-15 December 2009
Event Type
conference
Additional Information
ISBN: 978-142445223-1Source DOI: 10.1109/TECHPOS.2009.5412107