Generator maintenance scheduling of electric power systems using genetic algorithms with integer representation

1997 ◽  
Author(s):  
K.P. Dahal
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Electric Power ◽  
Electric Power Systems ◽  
Maintenance Scheduling ◽  
Integer Representation

scholarly journals POP analysis and optimization of a maintenance scheduling problem in electric power systems

2004 ◽  
Vol 37 (12) ◽  
pp. 837-840
Author(s):  
Yasumichi Sakoda ◽  
Keiichiro Yasuda
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Electric Power Systems ◽  
Maintenance Scheduling ◽  
Scheduling Problem

scholarly journals Optimization of modes of the electric power systems by genetic algorithms

2020 ◽  
Vol 216 ◽  
pp. 01099
Author(s):  
Behzod Pulatov ◽  
Shanazarov Alisher
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Power Systems ◽  
Electric Power ◽  
Shortest Path ◽  
Optimization Problems ◽  
Electric Power Systems ◽  
Data Filtering ◽  
Path Search ◽  
Shortest Path Search

In article discusses issues for solving optimization problems based on the use of genetic algorithms. Nowadays, the genetic algorithms for solving various problems. This includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc.

New genetic algorithms for contingencies selection in the static security analysis of electric power systems

2015 ◽  
Vol 42 (6) ◽  
pp. 2849-2856 ◽  
Author(s):  
José Vicente Canto dos Santos ◽  
Iverson Farias Costa ◽  
Thiago Nogueira
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Electric Power ◽  
Security Analysis ◽  
Electric Power Systems ◽  
Static Security

scholarly journals Locating High-Impedance Fault Section in Electric Power Systems Using Wavelet Transform,k-Means, Genetic Algorithms, and Support Vector Machine

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ying-Yi Hong ◽  
Wei-Shun Huang
Keyword(s):  
Support Vector Machine ◽  
Genetic Algorithms ◽  
Wavelet Transform ◽  
Power Systems ◽  
Electric Power ◽  
Fire Hazard ◽  
Electric Power Systems ◽  
Support Vector ◽  
Discrete Wavelet ◽  
High Impedance

High-impedance faults (HIFs) caused by downed conductors in electric power systems are in general difficult to be detected using traditional protection relays due to small fault currents. The energized downed conductor can pose a safety risk to the public and cause a fire hazard. This paper presents a new method for locating the line (feeder) section of the HIF with the help of limited measurements in electric power systems. The discrete wavelet transform is used to extract the features of transients caused by HIFs. A modifiedk-means algorithm associated with genetic algorithms is then utilized to determine the placement of measurement facilities. The signal energies attained by wavelet coefficients serve as inputs to the support vector machine for locating the HIF line section. The simulation results obtained from an 18-busbar distribution system show the applicability of the proposed method.

scholarly journals OPTIMIZATION OF MODES OF ELECTR POWER SYSTEMS BY GENETIC ALGOROTHMS

2019 ◽  
Vol 2019 (3) ◽  
pp. 224-229
Author(s):  
B Pulatov
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Power Systems ◽  
Electric Power ◽  
Optimization Problems ◽  
Block Diagram ◽  
Electric Power Systems ◽  
Data Filtering ◽  
Path Search ◽  
Shortest Path Search

In article discusses issues for solving optimization problems based on the use of genetic algorithms. To date, the genetic use algorithm for solving various problems. Which includes the shortest path search, approximation, data filtering and others. In particular, data is being examined regarding the use of a genetic algorithm to solve problems of optimizing the modes of electric power systems. Imagine an algorithm for developing the development of mathematical models, which includes developing the structure of the chromosome, creating a started population, creating a directing force for the population, etc. As well as the presentation, the selected structure should take into account all the features and limitations imposed on the desired solution, as well as the fact that the implementation of crossоver and mutation algorithms directly depends on its choice. To solve optimization problems, a block diagram of the genetic algorithm is given.

Optimal SVC placement in electric power systems using a genetic algorithms based method

2009 ◽  
Author(s):  
I. Pisica ◽  
C. Bulac ◽  
L. Toma ◽  
M. Eremia
Keyword(s):  
Genetic Algorithms ◽  
Power Systems ◽  
Electric Power ◽  
Electric Power Systems
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