Evaluation of Steady State Voltage Stability Margin of a Power System Using Search Group Algorithm
The rapid increase in load demand forces power systems to operate critically to meet the economic and environmental constraints. The stability margins are being further diminished in reacting to market pressures, which demand greater interest to reduce operating costs. The overall stability
limits are closely allied with the voltage stability of the network. Therefore, the voltage stability is a significant study in the operation and planning of a power system. This paper describes a metaheuristic algorithm, Search group algorithm (SGA) to determine the maximum loadability point
of the power system. The proposed algorithm aims at having a good balance between the exploration and exploitation of the design domain. The effectiveness of the proposed method is evaluated using the IEEE 118 bus system; prove its validity and applicability to other power system problems.
The results show that the Search group algorithm has a rapid convergence speed.
Keywords: Maximum Loadability Limit; Metaheuristic Algorithm; Particle Swarm Optimization; Search Group Algorithm (SGA); Voltage Stability
Document Type: Research Article
Affiliations: 1: Department of EEE, K. L. N. College of Engineering, Sivagangai 630612, Tamilnadu, India 2: Department of EEE, Syed Ammal Engineering College, Ramanathapuram 623502, Tamilnadu, India
Publication date: 01 November 2016
- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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