Genetic algorithm based optimization method for reactive power management
Institute of Power Engineering and Control Systems, Lviv Polytechnic National University, Lviv, Ukraine
Abstract
Reactive power management is a complicated and nonlinear problem. With the development of computer-based methods, some new methods have been proposed for this problem. The nature-based optimization algorithms are an efficient way of solving the nonlinear and not differentiable functions. One of the interesting of these algorithms is a genetic algorithm or GA. In this study, we proposed the application of a genetic algorithm for solving reactive power optimization. The proposed method must find the best parameters of power network including the generator node voltage, the transformers tap situation, and the parallel compensators value. In existing electrical power networks, these variables don’t consider and all capacity of the system didn’t use. In the traditional power network, the voltage profile is weak and the active power loss in transmission lines is high. With optimizing the reactive power control parameters, the voltage profile improved and the active power loss will be reduced significantly. In order to test the proposed system, the IEEE standard 25-node network is chosen. The simulation results show that the proposed method has a good effect on system performance.
Keywords
GA, Voltage, Reactive, Generators
Digital Object Identifier (DOI)
https://doi.org/10.21833/AEEE.2019.07.004
Article history
Received 18 February 2019, Received in revised form 15 June 2019, Accepted 15 June 2019
Full text
Available in PDF
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How to cite
Oliynyk F, Kolisnyk A, and Ponomarenko S (2019). Genetic algorithm based optimization method for reactive power management. Annals of Electrical and Electronic Engineering, 2(7): 16-21
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