A New Affine Arithmetic-Based Optimal Network Reconfiguration to Minimize Losses in a Distribution System Considering Uncertainty Using Binary Particle Swarm Optimization

2020 ◽  
Vol 48 (6-7) ◽  
pp. 628-639
Author(s):  
Vinod Raj ◽  
Boddeti Kalyan Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Distribution System ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Network Reconfiguration ◽  
Swarm Optimization ◽  
Affine Arithmetic ◽  
Optimal Network

Rekonfigurasi Jaringan Listrik Penyulang Tawun Rayon Ngawi Dengan Menggunakan Metode Binary Particle Swarm Optimization

2017 ◽  
Vol 8 (1) ◽  
pp. 1-10
Author(s):  
Muhammad Ruswandi Djalal ◽  
Herman Nawir ◽  
Sonong
Keyword(s):  
Particle Swarm Optimization ◽  
Load Balancing ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Network Reconfiguration ◽  
Loss Reduction ◽  
Swarm Optimization

Rekonfigurasi jaringan (Network Reconfiguration) merupakan suatu usaha merubah bentuk konfigurasi jaringan distribusi dengan mengoperasikan pensakelaran terkontrol jarak jauh (switching remotely controlled) pada jaringan distribusi tanpa menimbulkan akibat yang beresiko pada operasi dan bentuk sistem jaringan distribusi secara keseluruhan. Dalam kondisi operasi normal, rekonfigurasi jaringan dilakukan karena dua alasan: mengurangi rugi-rugi daya pada sistem (loss reduction), mendapatkan pembebanan yang seimbang untuk mencegah pembebanan yang berlebih pada jaringan (load balancing).  Pada Jarinyan Tegangan menengah Penyulang Tawun Rayon Ngawi terdiri dari 57 bus (GTT) dan 60 saluran. Dari hasil running menunjukkan bahwa sebelum rekonfigurasi memutus switch line 56, 57, 58, 59 dan 60 setelah rekonfigurasi line 26, 27, 42, 47 dan 53. Sebelum rekonfigurasi jaringan mengalami losses sebesar 235.1532 kW setelah rekonfigurasi mengalami losses sebesar 184.1323 kW. Hasil rekonfigurasi dapat mereduksi losses 21.6969 %. Dan tegangan ujung sebelum rekonfigurasi 0,93891 pu menjadi 0.95897 pu

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
Keyword(s):  
Particle Swarm Optimization ◽  
Distribution System ◽  
Distribution Network ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Electrical Network ◽  
Binary Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Good Efficiency ◽  
Voltage Loss

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.

scholarly journals Distribution System Reconfiguration for Loss Minimization and Voltage Profile Enhancement by using Discrete – Improved Binary Particle Swarm Optimization Algorithm

2019 ◽  
Vol 8 (2S11) ◽  
pp. 900-906
Keyword(s):  
Particle Swarm Optimization ◽  
Distribution System ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Voltage Profile ◽  
Power Losses ◽  
Swarm Optimization ◽  
System Reconfiguration ◽  
Distribution System Reconfiguration ◽  
Bus System

Distribution system reconfiguration is done by altering the open / close position of two kinds of switches: usually open tie switches and sectionalizing switches usually closed. Its main purpose is restoration of supply via other route to improve reliability, sometimes for load balancing by relieving overloads. Feeder reconfiguration is very good alternative to reduce power losses and improve voltage profile to improve overall performance. Distribution system reconfiguration is a very cost effective way to reduce the distribution system power losses, enhance voltage profile and system reliability. This paper presents application of novel Discrete - improved binary particle swarm optimization (D-IBPSO) algorithm for distribution system reconfiguration for minimization of real power loss and improvement of voltage profile. The algorithm is implemented to a 16-bus, 33-bus system and a 69-bus system considering different loading conditions. The simulation results indicate that the suggested technique can accomplish optimal reconfiguration and significantly reduce power losses on the supply scheme and enhance the voltage profile.

scholarly journals Power System Reconfiguration in Distribution Network for Improving Reliability Using Genetic Algorithm and Particle Swarm Optimization

2021 ◽  
Vol 11 (7) ◽  
pp. 3092
Author(s):  
Omar Kahouli ◽  
Haitham Alsaif ◽  
Yassine Bouteraa ◽  
Naim Ben Ali ◽  
Mohamed Chaabene
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Distribution System ◽  
Distribution Network ◽  
Mathematical Formulation ◽  
Particle Swarm ◽  
Network Reconfiguration ◽  
Power Losses ◽  
Swarm Optimization ◽  
Power Distribution System

This paper presents an optimal method for optimizing network reconfiguration problems in a power distribution system in order to enhance reliability and reduce power losses. Network reconfiguration can be viewed as an optimization problem involving a set of criteria that must be reduced when adhering to various constraints. The energy not supplied (ENS) during permanent network faults and active power losses are the objective functions that are optimized in this study during the reconfiguration phase. These objectives are expressed mathematically and will be integrated into various optimization algorithms used throughout the study. To begin, a mathematical formulation of the objectives to be optimized, as well as all the constraints that must be met, is proposed. Then, to solve this difficult combinatorial problem, we use the exhaustive approach, genetic algorithm (GA), and particle swarm optimization (PSO) on an IEEE 33-bus electrical distribution network. Finally, a performance evaluation of the proposed approaches is developed. The results show that optimizing the distribution network topology using the PSO approach contributed significantly to improving the reliability, node voltage, line currents, and calculation time.

Sign in / Sign up

Export Citation Format

Share Document