Naslov
Resilience Neural-Network-Based Methodology Applied on Optimized Transmission Systems Restoration

Autori
Tošić, Josip ; Skok, Srdjan ; Teklić, Ljupko ; Balković, Mislav

Izvornik
Energies (1996-1073) 15 (2022); 4694, 16

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
transmission power system optimization ; transmission system restoration ; artificial intelligence ; artificial neural networks ; power system analysis

Sažetak
This paper presents an advanced methodology for restoration of the electric power transmission system after its partial or complete failure. This load-optimized restoration is dependent on sectioning of the transmission system based on artificial neural networks. The proposed methodology and the underlying algorithm consider the transmission system operation state just before the fallout and, based on this state, calculate the power grid parameters and suggest the methodology for system restoration for each individual interconnection area. The novel methodology proposes an optimization objective function as a maximum load recovery under a set of constraints. The grid is analyzed using a large amount of data, which results in an adequate number of training data for artificial neural networks. Once the artificial neural network is trained, it provides an almost instantaneous network recovery plan scheme by defining the direct switching order.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA