Optimal Distribution System Reconfiguration Using Non-dominated Sorting Genetic Algorithm (NSGA-II)
Authors
Abstract:
In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method, 33-bus and 69-bus distribution networks have been employed which have led to the desired results.
similar resources
optimal distribution system reconfiguration using non-dominated sorting genetic algorithm (nsga-ii)
in this paper, a non-dominated sorting genetic algorithm-ii (nsga-ii) based approach is presented for distribution system reconfiguration. in contrast to the conventional ga based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. in order to illustrate the performance of the proposed method,...
full textOptimal Distribution System Reconfiguration Using Non- dominated Sorting Genetic Algorithm (NSGA-II)
In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...
full textVoltage Stability Constrained Optimal Power Flow Using Non-dominated Sorting Genetic Algorithm-II (NSGA II)
Voltage stability has become an important issue in planning and operation of many power systems. Contingencies such as unexpected line outages in a stressed system may often result in voltage instability, which may lead to voltage collapse. This paper presents evolutionary algorithm techniques like Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA II) approach for solv...
full textOptimal Placement of Phasor Measurement Units to Maintain CompleteObservability Considering Maximum Reliability by Non-dominated Sorting Genetic Algorithm-II (NSGA-II)
Ever-increasing energy demand has led to geographic expansion of transmission lines and their complexity. In addition, higher reliability is expected in the transmission systemsdue to their vital role in power systems. It is very difficult to realize this goal by conventional monitoring and control methods. Thus, phasor measurement units (PMUs) are used to measure system parameters. Although in...
full textPareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II
Reconfiguration, by exchanging the functional links between the elements of the system, represents one of the most important measures which can improve the operational performance of a distribution system. The authors propose an original method, aiming at achieving such optimization through the reconfiguration of distribution systems taking into account various criteria in a flexible and robust...
full textA Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II
Abstract. Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) computational complexity (where is the number of objectives and is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary algor...
full textMy Resources
Journal title
volume 1 issue 1
pages 12- 21
publication date 2007-06-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023