Heuristic optimization of PV energy penetration to resilience system frequency fluctuation

• Autorzy: Abbood, Afaneen Anwer , Habbi, Hanan Mikhael D.

Warianty tytułu

PL

Optymalizacja heurystyczna penetracji energii fotowoltaicznej w celu zapewnienia odporności na wahania częstotliwości systemu

• Języki publikacji: EN

Abstrakty

EN

Renewable energy can make the utility grid unstable by causing some problems, such as frequency fluctuations, voltage surges, and power instability because of the inconsistency of renewable energy resources. This paper focused on studying the effect of intermittent renewable energy represented by a PV-integrated grid on the frequency system response and grid voltage surge. Heuristic Optimization methods, Teaching learning-based optimization (TLBO), and particle swarm optimization (PSO) have been utilized to optimize the penetration of PV energy enhancing the supply frequency response. Both optimization methods have been implemented with different values of irradiance. Although they have similar performances, the simulation result showed that the TLBO method has a slightly better low-frequency oscillation than the PSO method. It is found that the TLBO algorithm presents a good power quality response of the grid-connected system. This is due to the fact of TLBO is faster than the PSO algorithm because it does not need specific parameters. The system is applied to a feeder in a distribution network in Baghdad power sector. The results are obtained by using the MATLAB package.

PL

Energia odnawialna może spowodować niestabilność sieci elektroenergetycznej, powodując pewne problemy, takie jak wahania częstotliwości, skoki napięcia i niestabilność mocy z powodu niespójności zasobów energii odnawialnej. W artykule skupiono się na badaniu wpływu przerywanej energii odnawialnej reprezentowanej przez zintegrowaną sieć fotowoltaiczną na odpowiedź systemu częstotliwości i udary napięcia sieciowego. Aby zoptymalizować przenikanie energii fotowoltaicznej, zwiększając charakterystykę częstotliwościową zasilania, zastosowano metody optymalizacji heurystycznej, optymalizacji opartej na uczeniu się (TLBO) i optymalizacji roju cząstek (PSO). Obie metody optymalizacji zostały zaimplementowane przy różnych wartościach natężenia napromieniowania. Chociaż mają one podobne właściwości, wynik symulacji pokazał, że metoda TLBO charakteryzuje się nieco lepszymi oscylacjami w zakresie niskich częstotliwości niż metoda PSO. Stwierdzono, że algorytm TLBO zapewnia dobrą odpowiedź dotyczącą jakości energii w systemie podłączonym do sieci. Wynika to z faktu, że TLBO jest szybszy od algorytmu PSO, ponieważ nie wymaga określonych parametrów. System stosowany jest w polu zasilającym w sieci dystrybucyjnej w sektorze energetycznym Bagdadu. Wyniki uzyskuje się za pomocą pakietu MATLAB.

Słowa kluczowe

PL

dystrybucja systemu elektroenergetycznego; wahanie częstotliwości; optymalizacja oparta na nauczaniu; TLBO; PSO

EN

power system distribution; frequency fluctuation; teaching-learning-based optimization; TLBO; PSO

• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2023
• Tom: R. 99, nr 12
• Strony: 40--44
• Opis fizyczny: Bibliogr. 23 poz., rys.

Twórcy

autor

Abbood, Afaneen Anwer

• University of Technology-Iraq, Baghdad

autor

Habbi, Hanan Mikhael D.

• University of Baghdad, Dept. Of Electrical Engineering, Baghdad, Iraq

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Identyfikatory

DOI

10.15199/48.2023.12.07