| Summary: | 碩士 === 中州科技大學 === 工程技術研究所 === 102 === In development of power system, stability has been very important considerations. This paper aims to enhance power system stability by intelligent control. In the area of intelligent control, searching rule has been divided into Recursive and Iterative. Design fuzzy control by Advanced Continuous Ant Colony Optimization (ACACO) is proposed in this paper.
The fundamental idea underlying Continuous Ant Colony Optimization (CACO) is a probability density function (PDF). ACACO, following the evolution way of Genetic Algorithm (GA) can generated at each iteration T new solutions together with the original N solutions in the colony, which is re-ordered from the best to worst according their cost values. For ACACO works a fixed colony size of N, only the top N solutions are reserved in the colony and the left T solutions are discarded.
Flexible AC Transmission System (FACTS) and Load Frequency Control (LFC) by ACACO are applied to demonstrate the feasibility of the proposed methods. In the application on FACTS, a comparison is made between conventional fixed parameter controller and Genetic Particle Swarm Optimization (GPSO) algorithms to verify the performance of the proposed approach. In the application on LFC, simulations on a three-area interconnected power system with different kinds of perturbations were compared with that on Particle Swarm Optimization (PSO) and Elitist Genetic Algorithm (EGA), and so on. The performance of the proposed approach is verified.
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