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Optimal Distributed Generation Placement in Distribution Network


Vukobratović, Marko; Hederić, Željko; Hadžiselimović, Miralem
Optimal Distributed Generation Placement in Distribution Network // Proceedings EnergyCon 2014 - IEEE International Energy Conference / Kuzle, Igor ; Capuder, Tomislav ; Pandžić, Hrvoje ; (ur.).
Red Hook, NY 12571 USA: IEEE, 2014. str. 1236-1243 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Optimal Distributed Generation Placement in Distribution Network

Autori
Vukobratović, Marko ; Hederić, Željko ; Hadžiselimović, Miralem

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings EnergyCon 2014 - IEEE International Energy Conference / Kuzle, Igor ; Capuder, Tomislav ; Pandžić, Hrvoje ; - Red Hook, NY 12571 USA : IEEE, 2014, 1236-1243

ISBN
978-1-4799-2448-6

Skup
EnergyCon 2014 - IEEE International Energy Conference

Mjesto i datum
Dubrovnik, Hrvatska, 13-16.05.2014.

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Distributed generation; Artificial Neural Networks; Genetic Algorithm; Voltage control; Power losses reduction.

Sažetak
Abstract— this paper presents a method for optimal Distributed Generation placement with goal of reducing active power system losses and voltage level regulation. Active power losses in radial distribution network are determined using an Artificial Neural Network (ANN) by simultaneous formulation for the determination process based on voltage level control and injected power. Adequate installed power of distributed generation and the appropriate terminal for distributed generation utilization are selected by means of a genetic algorithm (GA), performed in a distinct manner that fits the type of decision-making assignment. The training data for ANN is obtained by means of load flow simulation performed in DIgSILENT PowerFactory software on a part of the Croatian distribution network. The active power losses and voltage conditions are simulated for various operation scenarios in which the back propagation ANN model has been tested to predict the power losses and voltage levels for each system terminal, and GA is used to determine the optimal terminal for distributed generation placement.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

Napomena
DOI: 10.1109/ENERGYCON.2014.6850572



POVEZANOST RADA


Ustanove
Edukacijsko-rehabilitacijski fakultet, Zagreb,
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek