Evolutionary programming based optimal power flow algorithm

This paper develops an efficient and reliable evolutionary programming algorithm for solving the optimal power flow (OPF) problem. The class of curves used to describe generator performance does not limit the algorithm and the algorithm is also less sensitive to starting points. To improve the speed...

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Bibliographic Details
Published inIEEE transactions on power systems Vol. 14; no. 4; pp. 1245 - 1250
Main Authors Yuryevich, J., Kit Po Wong
Format Journal Article
LanguageEnglish
Published IEEE 01.11.1999
Subjects
Acceleration
Algorithms
Buses (vehicles)
Constraint optimization
Convergence
Costs
Evolutionary algorithms
Generators
Genetic programming
Handles
Load flow
Optimization
Power flow
Power system analysis computing
Power system economics
Power system reliability
Power systems
System testing
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ISSN0885-8950
DOI10.1109/59.801880

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Summary:This paper develops an efficient and reliable evolutionary programming algorithm for solving the optimal power flow (OPF) problem. The class of curves used to describe generator performance does not limit the algorithm and the algorithm is also less sensitive to starting points. To improve the speed of convergence of the algorithm as well as its ability to handle larger systems, the algorithm is enhanced with gradient information. In the paper, the main elements of the evolutionary programming based OPF algorithm are presented. The algorithm is then demonstrated on the IEEE 30 bus test system.
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ISSN:0885-8950
DOI:10.1109/59.801880