Rekonfigurasi Jaringan Menggunakan Binary Particle Swarm Optimization (BPSO) Pada Penyulang Suryagraha

2020 ◽  
Vol 1 (1) ◽  
pp. 22-30
Author(s):  
Diana Mulya Dewi ◽  
Nuzul Hikmah ◽  
Imam Marzuki ◽  
Ahmad Izzuddin

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the endpoint. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees, or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of bits to reach value 1. The results show a significant reduction in losses.

2019 ◽  
Vol 9 (2) ◽  
pp. 58-66
Author(s):  
Diana Mulya Dewi ◽  
Nuzul Hikmah ◽  
Imam Marzuki ◽  
Ahmad Izzuddin

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the end point. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of xn bits to reach value 1. The results show a significant reduction in losses .


2018 ◽  
Vol 9 (2) ◽  
pp. 58-66
Author(s):  
Diana Mulya Dewi ◽  
Nuzul Hikmah ◽  
Imam Marzuki ◽  
Ahmad Izzuddin

A radial distribution electrical network at a certain distance will have a large voltage loss due to conductive losses, especially at the end point. The tip voltage is determined by the distance of the distribution and the amount of load. The form of configuration also affects the amount of power loss and voltage loss. So that a good configuration is needed in order to obtain good efficiency. Reconfiguration of the distribution network is used to reset the network configuration form by opening and closing switches on the distribution network. Reconfiguration is expected to reduce power losses and improve distribution system reliability. Many feeders and buses on the network if calculated manually will be difficult and require a very long time. So it is necessary to solve problems using program assistance. In this case, use Particle Swarm Optimization (PSO). Particle Swarm Optimization (PSO) algorithm based on the behavior of a herd of insects, such as ants, termites, bees or birds. BPSO is a development of the PSO algorithm designed to solve the optimization problem in a discrete combination, where the particle takes the value of binary vectors with length n and speed which is defined as the probability of xn bits to reach value 1. The results show a significant reduction in losses.


2020 ◽  
Vol 20 (3) ◽  
pp. 937-949
Author(s):  
Min Zhao ◽  
Yan-Fang Zhang

To meet the requirement of the efficiency and accuracy for fault section location introduced by the construction and development of smart distribution network containing DG, a switching function model which can adapt itself to the change caused by switching of multiple DG is built and a network regional processing solution is raised. A fault section location for distribution network containing DG based on improved binary quantum particle swarm optimization (IBQPSO), which can effectively overcome the problem of global and local search capability imbalance in binary particle swarm optimization (BPSO), is proposed. The fault tolerance, rapidity and accuracy of this method are verified by simulation analysis of IEEE33 node system containing DG.


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