Optimal Power Flow Method Using Evolutionary Programming

Authors:
Kit Po Wong;Jason Yuryevich
Affiliations:
-;-
Venue:
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Year:
1998

Citing 4
Cited 1

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Evolutionary computation: toward a new philosophy of machine intelligence

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Evolution and Optimum Seeking: The Sixth Generation

Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning

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Optimal allocation and sizing of SSSC controller to minimise power production cost and transmission loss

International Journal of Computational Science and Engineering

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Abstract

This paper reports on an evolutionary programming based method for solving the optimal power flow problem. The method incorporates an evolutionary programming based load flow solution. To demonstrate the global optimisation power of the new method it is applied to the IEEE30 bus test system with highly non-linear generator input/output cost curves and the results compared to those obtained using the method of steepest descent. The results demonstrate that the new method shows great promise for solving the optimal power flow problem when it contains highly non-linear devices.