Multi-objective ant lion optimizer for solving environmental/economic dispatch

• Autorzy: Hardiansyah Hardiansyah , Junaidi Junaidi

Identyfikatory

DOI

10.15199/48.2021.02.32

Warianty tytułu

PL

ieloobiektowy algorytm mrowkolwowaty do rozwiązywania problemu ekonomicznego rozsyłu energii z uwzględnieniem środowiska

• Języki publikacji: EN

Abstrakty

EN

In this paper, a new meta-heuristic algorithm, called multi-objective ant lion optimizer (MOALO) is presented to solve environmental economic dispatch (EED) problem considering transmission losses. MOALO is inspired by the hunting mechanism of ant lions in nature. It has fast convergence speed due to the use of roulette wheel selection technique. The effectiveness of the proposed algorithm has been tested on the standard IEEE 30-bus test system and the results were compared with other methods reported in recent literature. The simulation results show that the proposed algorithm outperforms previous optimization methods.

PL

Przedstawiono nowy meta-heurystyczny algorytm MOALO do rozwiązywania problemu ekonomicznego rozsyłu energii z uwzględnieniem warunków środowiskowych. Algorytm jest inspirowany mechanizmem polowania. Daje on szybkie rozwiązanie z wykorzystaniem zasady koła w ruletce. Algorytm sprawdzono wykorzystując system testowy IEEE-30-bus.

Słowa kluczowe

EN

multi-objective ant lion optimizer; economic dispatch; emission dispatch; combined economic emission dispatch

PL

rozsył energii ekonomiczny; owady mrówkolwaowate; emisja zanieczyszczeń

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2021
• Tom: R. 97, nr 2
• Strony: 153--158
• Opis fizyczny: Bibliogr. 26 poz., rys., tab.

Twórcy

autor

Hardiansyah Hardiansyah

• Faculty of Engineering, University of Tanjungpura, Pontianak 78124, Indonesia

autor

Junaidi Junaidi

• Faculty of Engineering, University of Tanjungpura, Pontianak 78124, Indonesia

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).