power system stability improvement via tcsc controller employing a multi-objective strength pareto evolutionary algorithm approach
Authors
abstract
this paper focuses on multi-objective designing of multi-machine thyristor controlled series compensator (tcsc) using strength pareto evolutionary algorithm (spea). the tcsc parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a spea algorithm. the effectiveness of the proposed controller validates on a multi-machine power system over a wide range of loading conditions. the results of the proposed controller (speatcsc) are compared with the genetic algorithm (ga) based tuned tcsc through some operating conditions to demonstrate its superior efficiency.
similar resources
Power System Stability Improvement via TCSC Controller Employing a Multi-objective Strength Pareto Evolutionary Algorithm Approach
This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...
full textPower System Stability Improvement via TCSC Controller Employing a Multi-objective Strength Pareto Evolutionary Algorithm Approach
This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...
full textPower System Stability Improvement by TCSC Controller Employing a Multi - Objective Genetic Algorithm Approach
Algorithm (GA) approach to tune the parameters of a Thyristor Controlled Series Compensator (TCSC), for power system stability improvement. Pareto method type of selection is used in the present multi-objective GA approach, which gives a set of solutions from which the best one can be chosen according to the requirements and needs. The design problem of TCSC controller is formulated as a parame...
full textEvolving Optimal Multi-Objective Hardware Using Strength Pareto Evolutionary Algorithms
In this paper, we focus on engineering Pareto-optimal digital circuits given the expected input/output behaviour with a minimal design effort. The design objectives to be minimised are: hardware area, response time and power consumption. We do so using the Strength Pareto Evolutionary Algorithms. This is novel application of multi-objective optimisation to circuit design. The performance and qu...
full textAn Approach Based on the Strength Pareto Evolutionary Algorithm 2 for Power Distribution System Planning
The vast majority of the developed planning methods for power distribution systems consider only one objective function to optimize. This function represents the economical costs of the systems. However, there are other planning aspects that should be considered but they can not be expressed in terms of costs; therefore, they need to be formulated as separate objective functions. This paper pre...
full textmulti-machine power system stability improvement using a new fuzzy wavelet neural network damping controller
this paper presents a new damping controller design based on fuzzy wavelet neural network (fwnn) to damp the multi-machine power system low frequency oscillations. the error between the desired system output and the output of control object is directly utilized to tune the network parameters. the orthogonal least square (ols) algorithm is used to purify the wavelets for each rule and determine ...
full textMy Resources
Save resource for easier access later
Journal title:
journal of operation and automation in power engineeringPublisher: university of mohaghegh ardabili
ISSN 2322-4576
volume 1
issue 1 2007
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023