Original scientific paper

https://doi.org/10.17559/TV-20130618144654

Voltage and power losses control using distributed generation and computational intelligence

Marko Vukobratović orcid.org/0000-0001-8596-6426 ; J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Power System Department, Kneza Trpimira 2b, 31 000 Osijek, Croatia
Predrag Marić orcid.org/0000-0003-0099-2743 ; J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Power System Department, Kneza Trpimira 2b, 31 000 Osijek, Croatia
Željko Hederić orcid.org/0000-0001-7265-0932 ; J. J. Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Power System Department, Kneza Trpimira 2b, 31 000 Osijek, Croatia

Abstract

The paper analyzes the possibility of reducing active power losses in power system, constrained by regulated voltage levels, by implementing appropriate distributed generation capacity. The objectives of this paper were achieved by developing hybrid methods based on artificial neural network and genetic algorithm. Methods have been developed to determine the impact of different distributed generation power on all terminals in the observed system. The method that uses artificial neural network and genetic algorithm is applicable for radial distribution networks, and method using load flow and genetic algorithm is applicable to doubly-fed distribution network. For comparison purposes, additional method was developed that uses neural networks for the decision-making process. Data for training the neural network was obtained by power flow calculation in the DIgSILENT PowerFactory software on a part of Croatian distribution network. The same software was used as an analytical tool for checking the correctness of solutions obtained by optimization.

Keywords

artificial neural networks; distributed generation; genetic algorithm

Hrčak ID:

163809

URI

https://hrcak.srce.hr/163809

Publication date:

16.8.2016.

Article data in other languages: croatian

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