Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm
DOI:
https://doi.org/10.31436/iiumej.v23i2.2190Keywords:
distribution network reconfiguration (DNR), multi-objective Cuckoo Search (MOCS) algorithm, power loss reduction, switch operations, Pareto optimalAbstract
In power system electricity delivery, the distribution system has the most electricity loss as the system has the highest R/X ratio and has a radial network at one time. Optimal reconfiguration of the distribution network is needed in order to reduce power losses. However, as it is also involved with multiple objectives and constraint problems such as switching frequency, voltage, and current limits, it is difficult to find the optimal solution. Hence, this paper proposes the Multi-objective Cuckoo Search (MOCS) algorithm to find the optimal reconfiguration of distribution networks by considering minimizing power losses and switch operations. Based on the simulation results on the IEEE-33 bus system, the performance of the MOCS-based scheme has been found to be significantly better than the single-objective algorithm thereby reducing approximately 33% of the power losses.
ABSTRAK Melalui sistem penghantaran jana kuasa elektrik, sistem pengagihan mempunyai pembaziran tenaga elektrik terbesar kerana sistem ini mempunyai nisbah R/X paling tinggi dan mempunyai satu rangkaian radial pada tiap-tiap satu masa. Konfigurasi semula rangkaian pengedaran yang optimum diperlukan bagi mengurangkan pembaziran tenaga. Walaubagaimanapun, oleh kerana ia melibatkan objektif dan kekangan masalah yang pelbagai seperti kadar peralihan, had voltan serta arus, adalah sukar bagi mendapatkan bacaan yang optimum. Oleh itu, kajian ini mencadangkan Carian Cuckoo Pelbagai Objektif (MOCS) bagi mencari konfigurasi semula yang optimum bagi sistem pengagihan tenaga dengan mengambil kira pengurangan pembaziran tenaga dan kadar peralihan. Berdasarkan keputusan simulasi pada sistem bas IEEE-33, pretasi MOCS telah menunjukkan peningkatan yang ketara berbanding algoritma objektif tunggal dan pengurangan sebanyak 33% tenaga.
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