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EN
Feeder reconfiguration (FR), capacitor placement and sizing (CPS) are the two renowned methods widely applied by the researchers for loss minimization with node voltage enrichment in the electrical distribution network (EDN), which has an immense impact on economic savings. In recent years, optimization of FR and CPS together can proficiently yield better power loss minimization and save costs compared to the individual optimization of FR and CPS. This work proposes an application of an improved salp swarm optimization technique based on weight factor (ISSOT-WF) to solve the cost-based objective function using CPS with and without FR for five different cases and three load levels, subject to satisfying operating constraints. In addition, to ascertain the impact of real power injection on additional power loss reduction, this work considers the integration of dispersed generation units at three optimal locations in capacitive compensated optimal EDN. The effectiveness of ISSOT-WF has been demonstrated on the standard PG&E-69 bus system and the outcomes of the 69-bus test case have been validated by comparing with other competing algorithms. Using FR and CPS at three optimal nodes and due to power loss reduction, cost-saving reached up to a maximum of 71%, and a maximum APLR of 26% was achieved after the installation of DGs at three optimal locations with the significant improvement in the bus voltage profile.
EN
The work is intended to extend the application of a smart transformer on a radialdistribution system. In this paper, an updated algorithm on the backward/forward powerflow is introduced. The so-called direct approach of power flow is employed and analyzed.In addition, the paper focused on integrating a smart transformer to the network and solvingthe updating network also using the direct approach load flow. The solution of the smarttransformer using the direct approach power flow method is quite straightforward. Thismodel is applied to radial distribution systems which are the IEEE 33- and IEEE 69-bussystems as a case study. Also, the paper optimizes the best allocation of the smart transformerto reduce the power losses of the grid.
EN
This paper present a novel optimization method, Time Varying Acceleration – Rank Evolutionary Particle Swarm Optimization (TVAREPSO) in solving optimum generator sizing for minimising power losses in the transmission system of South Sulawesi, Indonesia. A comparison between the proposed method and three other methods was done in order to find the best method to optimize the generators’ output size. The results show that the TVA-REPSO algorithm can obtain the same performance as PSO but it only required shorter computing time and can converges faster than the original PSO.
PL
W artykule przedstawiono matematyczną metodę rozwiązania zagadnienia znalezienia optymalnego rozmiaru generatora, w celu minimalizacji strat w elektroenergetycznym systemie przesyłowym Południowej Sulawesi w Indonezji. W algorytmie wykorzystano optymalizację roju cząstek ze zmiennym w czasie przyspieszeniem (ang. TVA-REPSO). Dokonano porównania z innymi metodami, pokazało, że opracowana metoda ma skuteczność podobną do klasycznej metody PSO, lecz krótszy czas obliczeń.
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