Tehnički vjesnik, Vol. 23 No. 4, 2016.
Izvorni znanstveni članak
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
Sažetak
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.
Ključne riječi
artificial neural networks; distributed generation; genetic algorithm
Hrčak ID:
163809
URI
Datum izdavanja:
16.8.2016.
Posjeta: 2.263 *