Abstract: Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.
Abstract: Although the usefulness of fuzzy databases has been
pointed out in several works, they are not fully developed in numerous
domains. A task that is mostly disregarded and which is the topic
of this paper is the determination of suitable inequalities for fuzzy
sets in fuzzy query languages. This paper examines which kinds
of fuzzy inequalities exist at all. Afterwards, different procedures
are presented that appear theoretically appropriate. By being applied
to various examples, their strengths and weaknesses are revealed.
Furthermore, an algorithm for an efficient computation of the selected
fuzzy inequality is shown.