Hybrid of lambda iteration and meta-heuristic methods for solving economic dispatch problem

• Autorzy: Aurasopon Apinan , Takeang Chiraphon

Identyfikatory

DOI

10.15199/48.2020.06.05

Warianty tytułu

PL

Hybrydowy algorytm optymalizacji ekonomicznego rozsyłu energii wykorzystujący iterację lambda i metodę meta-heurystyczną

• Języki publikacji: EN

Abstrakty

EN

New optimization algorithms for solving the economic dispatch problem are presented. The constraints of economic dispatch consist of power balance, generator rating, load demand, and transmission loss. In the proposed algorithms, a lambda iteration method is used to find the initial values for the meta-heuristic methods: BCO, PSO, and GA. This process results in the solution boundary being reduced. To verify the effectiveness of the proposed algorithm, two case studies with three and six generators were tested. The simulation results showed that the proposed algorithms can provide better solutions than the others in terms of convergence rate and generation outputs.

PL

Przedstawiono nową technikę optymalizacji umożliwiająca zwiększenie skuteczności ekonomicznego rozsyłu energii. Uwzględnia on równowagę mocy, ocenę generatora, wymagane obciążenia oraz straty przesyłania. Proponowana metoda jest hybrydową iteracją lambda oraz metodą meta-heurystyczną wykorzystującą algorytmy genetyczne. Przetestowano dwa przypadki układu z trzema i sześcioma generatorami.

Słowa kluczowe

EN

economic dispatch; lambda iteration; meta-heuristic; optimization

PL

ekonomiczny rozsył energii; optymalizacja; iteracja lambda

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2020
• Tom: R. 96, nr 6
• Strony: 26--32
• Opis fizyczny: Bibliogr. 31., rys., tab.

Twórcy

autor

Aurasopon Apinan

• Faculty of Engineering, Mahasarakham University, Mahasarakham 44150, Thailand

autor

Takeang Chiraphon

• Faculty of Engineering, Rajamangala University of Technology Lanna, Lampang, Lampang 52000, Thailand

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 (2020).