Distribution Network Reconfiguration to Reduce Losses Using Intelligent Teaching-Learning Based Algorithm
سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 466
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شناسه ملی سند علمی:
NPECE01_332
تاریخ نمایه سازی: 6 بهمن 1395
چکیده مقاله:
In this paper, reconfiguration of radial distribution network is done using two evolutionary optimization methods under the headings Bacterial Forging optimization and Teaching-Learning-Based Optimization (TLBO). In this study, the objective function of the reconfiguration problem is considered as minimizing the amount of total losses in the network. Load on the network is investigated in three modes normal load, low load and overload. Voltage profile of the network is evaluated after the network reconfiguration in the different load conditions. Simulation results show that the TLBO method is more powerful way to find the best configuration of network and has shown better or same performance in reduction of network losses compared to the bacterial forging optimization (BFO), tabu search (TS), simulated annealing (SA) and modified particle swarm optimization (MPSO) .
کلیدواژه ها:
نویسندگان
Javad khanbabazadeh
Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran.
Armin Arasteh
Department of Electrical Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran