Investigation of load variant under power distribution network reconfiguration using EPSO algorithm

• Autorzy: Long Wong Kok , Sulaiman Mohamad Fani , Nasir Mohamad Naim Mohd , Bohari Zulhasrizal

Identyfikatory

DOI

10.15199/48.2024.05.22

Warianty tytułu

PL

Badanie wariantu obciążenia w ramach rekonfiguracji sieci dystrybucyjnej przy użyciu algorytmu EPSO

• Języki publikacji: EN

Abstrakty

EN

Recently, the power loss issue has emerged as a critical challenge, causing significant disruptions in the nation's infrastructure, economy, and daily lives of its citizens. Despite being a rapidly developing country with a growing demand for electricity, frequent instances of power loss and interruption have resulted in severe consequences such as reduced productivity, financial losses, compromised public safety, and increased inconvenience to individuals and businesses. Due to that reason, this study proposes the Evolutionary Particle Swarm Optimization (EPSO) algorithm which is a hybrid optimization technique that combines the principles of Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) to solve optimization problems by reducing the power losses under Distribution Network Reconfiguration (DNR). Moreover, the consideration of load variants involved in DNR while validating the voltage profile improvement with the best load weightage has been made concurrently. A detailed performance analysis is carried out on IEEE 33-bus test systems to demonstrate the effectiveness of the proposed method. Through simultaneous optimization, it was found that power loss reduction was achieved after conducting power DNR in a radial network connection. Furthermore, the test result also indicated that the EPSO algorithm produced better results in terms of convergence time compared to the conventional PSO algorithm.

PL

Ostatnio problem utraty mocy stał się krytycznym wyzwaniem, powodującym znaczne zakłócenia w krajowej infrastrukturze, gospodarce i codziennym życiu obywateli. Pomimo tego, że jest to kraj szybko rozwijający się o rosnącym zapotrzebowaniu na energię elektryczną, częste przypadki utraty i przerw w dostawie energii powodują poważne konsekwencje, takie jak zmniejszenie produktywności, straty finansowe, zagrożenie bezpieczeństwa publicznego oraz zwiększone niedogodności dla osób fizycznych i przedsiębiorstw. Z tego powodu w niniejszym badaniu zaproponowano algorytm Evolutionary Particle Swarm Optimization (EPSO), który jest hybrydową techniką optymalizacji, która łączy w sobie zasady programowania ewolucyjnego (EP) i optymalizacji roju cząstek (PSO) w celu rozwiązania problemów optymalizacyjnych poprzez zmniejszenie strat mocy w warunkach Rekonfiguracja sieci dystrybucyjnej (DNR). Co więcej, równolegle uwzględniono warianty obciążenia związane z DNR podczas walidacji poprawy profilu napięcia przy najlepszym obciążeniu. Szczegółowa analiza wydajności jest przeprowadzana na systemach testowych IEEE 33-bus, aby wykazać skuteczność proponowanej metody. Dzięki jednoczesnej optymalizacji stwierdzono, że redukcję strat mocy uzyskano po przeprowadzeniu zasilania DNR w promieniowym połączeniu sieciowym. Ponadto wynik testu wskazał również, że algorytm EPSO dał lepsze wyniki pod względem czasu zbieżności w porównaniu z konwencjonalnym algorytmem PSO.

Słowa kluczowe

EN

evolutionary particle swarm optimization; particle swarm optimization; distribution network reconfiguration; load variant

PL

ewolucyjna optymalizacja roju cząstek; optymalizacja roju cząstek; rekonfiguracja sieci dystrybucyjnej

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 5
• Strony: 124--128
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Long Wong Kok

• Universiti Teknikal Malaysia Melaka, Fakulti Teknologi Kejuruteraan Elektrik

autor

Sulaiman Mohamad Fani

• Universiti Teknikal Malaysia Melaka, Fakulti Teknologi Kejuruteraan Elektrik

autor

Nasir Mohamad Naim Mohd

• Universiti Teknikal Malaysia Melaka, Fakulti Teknologi Kejuruteraan Elektrik

autor

Bohari Zulhasrizal

• Universiti Teknikal Malaysia Melaka, Fakulti Teknologi Kejuruteraan Elektrik

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).