Pregled bibliografske jedinice broj: 686127
Optimization Method for Control of Voltage Level and Active Power Losses Based on Optimal Distributed Generation Placement using Artificial Neural Networks and Genetic Algorithms
Optimization Method for Control of Voltage Level and Active Power Losses Based on Optimal Distributed Generation Placement using Artificial Neural Networks and Genetic Algorithms // Journal of energy technology, 6 (2013), 4; 11-30 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 686127 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Optimization Method for Control of Voltage Level and Active Power Losses Based on Optimal Distributed Generation Placement using Artificial Neural Networks and Genetic Algorithms
Autori
Vukobratović, Marko ; Marić, Predrag ; Hederić, Željko
Izvornik
Journal of energy technology (1855-5748) 6
(2013), 4;
11-30
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Distributed Generation ; Artificial Neural Network ; Genetic Algorithm ; Voltage Control
Sažetak
This paper presents a method for reducing active power system losses and voltage level regulation by implementing adequate distributed generation capacity on the appropriate terminal in a distribution system. Active power losses are determined using an Artificial Neural Network (ANN) using 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 Artificial Neural Network (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 artificial neural network 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
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek
Profili:
Predrag Marić
(autor)
Citiraj ovu publikaciju:
Uključenost u ostale bibliografske baze podataka::
- INSPEC
- Cambridge Scientific Abstracts: Abstracts in New Technologies and Engineering (CSA ANTE)
- ProQuest's Technology Research Database