scholarly journals Optimal Reconfiguration of Distribution Networks Using Hybrid Heuristic-Genetic Algorithm

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1544 ◽  
Author(s):  
Damir Jakus ◽  
Rade Čađenović ◽  
Josip Vasilj ◽  
Petar Sarajčev
Keyword(s):  
Distribution Network ◽  
Distribution Networks ◽  
Total Power ◽  
Computational Time ◽  
Small Scale ◽  
Network Reconfiguration ◽  
Optimal Distribution ◽  
Voltage Profile ◽  
Distribution Network Reconfiguration ◽  
Optimal Reconfiguration

This paper describes the algorithm for optimal distribution network reconfiguration using the combination of a heuristic approach and genetic algorithms. Although similar approaches have been developed so far, they usually had issues with poor convergence rate and long computational time, and were often applicable only to the small scale distribution networks. Unlike these approaches, the algorithm described in this paper brings a number of uniqueness and improvements that allow its application to the distribution networks of real size with a high degree of topology complexity. The optimal distribution network reconfiguration is formulated for the two different objective functions: minimization of total power/energy losses and minimization of network loading index. In doing so, the algorithm maintains the radial structure of the distribution network through the entire process and assures the fulfilment of various physical and operational network constraints. With a few minor modifications in the heuristic part of the algorithm, it can be adapted to the problem of determining the distribution network optimal structure in order to equalize the network voltage profile. The proposed algorithm was applied to a variety of standard distribution network test cases, and the results show the high quality and accuracy of the proposed approach, together with a remarkably short execution time.

scholarly journals Improvement methods for solving the distribution network reconfiguration problem

Energetika ◽  
2019 ◽  
Vol 64 (4) ◽  
Author(s):  
Ha Duc Nguyen ◽  
Ilgiz Mirgalimovich Valeev
Keyword(s):  
Large Scale ◽  
Heuristic Algorithms ◽  
Distribution Network ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Distributed Generations ◽  
Distribution Network Reconfiguration ◽  
Radial Distribution Networks ◽  
Active Power Losses

The paper presents methods for solving the distribution network reconfiguration problem based on heuristic algorithms. In particular, the study solved the distribution network reconfiguration problem for active power losses reduction. The application of the method to a sample network proved effective compared to other algorithms, especially in case of large-scale and complex systems. In addition, the paper considers the influence of the location and capacity of distributed generations on the distribution network reconfiguration problem in different cases. The results show that the distribution network reconfiguration problem combined with optimization location and size of distributed generations is the most efficient solution for minimizing power loss and enhancing voltage profile. The proposed methods have been also successfully applied in the small- and medium-scale practical radial distribution networks. The simulation results show that the proposed methods can be used as reference materials for network reconfiguration problems with single and multi-objectives.

Power Distribution Network Reconfiguration by Using EPSO for Loss Minimizing

2014 ◽  
Vol 699 ◽  
pp. 809-815 ◽  
Author(s):  
Mohamad Fani Sulaima ◽  
Mohd Hafiz Jali ◽  
Wan Mohd Bukhari ◽  
M.N.M. Nasir ◽  
Hazriq Izzuan Jaafar
Keyword(s):  
Particle Swarm Optimization ◽  
Power Distribution ◽  
Distribution Network ◽  
Heuristic Method ◽  
Particle Swarm ◽  
Computational Time ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Power Distribution Network ◽  
Swarm Optimization

Due to the complexity of modern power distribution network, a hybridization of heuristic method which is called as Evolutionary Particle Swarm Optimization (EPSO) is introduced to identify the open and closed switching operation plans for network reconfiguration. The objectives of this work are to reduce the power losses and improve the voltage profile in the overall system meanwhile minimizing the computational time. The proposed combination of Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) is introduced to make it faster in order to find the optimal solution. The proposed method is applied and it impacts to the network reconfiguration for real power loss and voltage profiles is investigated respectively. The proposed method is tested on a IEEE 33-bus system and it is compared to the traditional PSO and EP method accordingly. The results of this study is hoped to help the power engineer to configure the smart and less lossed network in the future.

scholarly journals Evaluation of Linear-Load Modelling Effects on Distribution Network Reconfiguration in the Presence of Harmonic Loads

2021 ◽  
Author(s):  
MohamadAli Amini
Keyword(s):  
Harmonic Analysis ◽  
Power Quality ◽  
Distribution Network ◽  
Harmonic Distortion ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Distribution Network Reconfiguration ◽  
Optimum Configuration ◽  
Linear Load ◽  
Comparison Results

Recently, Power Quality is attracting the attention of researchers focused on distribution network reconfiguration. Mainly, harmonic distortion as an emerging issue of distribution networks plays an essential role in power quality-oriented network reconfiguration. Commonly, harmonic analysis of distribution networks is being performed while considering non-linear loads, capacitor banks, sub-transmission transformers, and line impedances. However, in harmonic analysis, the presence of linear loads and their effects are being neglected. Consideration of linear loads in harmonic analysis affects the impedance characteristic of the distribution network. Consequently, it changes the total harmonic distortion of bus voltages. In this paper, for the first time, exhaustive research is performed on the effect of linear loads in distribution network reconfiguration by considering five conventional linear load models. The evaluations are conducted on two balanced and unbalanced distribution networks: IEEE 69-bus and 95-bus practical Iranian distribution network using particle swarm optimization aiming to find the minimum total losses of the network. Comparison results confirm that the linear load modelling is very effective in the optimum configuration.

scholarly journals Impact of Network Reconfiguration: Case Study of Port-Harcourt Town 132/33kV Sub-transmission Substation and Its 33/11kV Injection Substation Distribution Networks

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Chinweike Innocent Amesi ◽  
Tekena Kashmony Bala ◽  
Anthony O. Ibe
Keyword(s):  
Power Flow ◽  
Low Voltage ◽  
Distribution Networks ◽  
Total Power ◽  
Base Case ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Distribution Transformers ◽  
Port Harcourt ◽  
Bus Voltage

This paper examined the power flow status of the Port Harcourt Town (Zone 4) distribution networks to improve the performance. The network consists of 18 injection substations fed from 4 different sizes of transformers with a total power rating of 165 MVA, 132/33kV at the Port Harcourt Town sub-transmission substation. Gauss-seidel power flow algorithm was used to analyse the network in Electrical Transient Analyzer Program software (ETAP 12.6) to determine the various bus operating voltages, power flow, and over or under-loaded Transformers’ units. From the base-case simulation results obtained, it shows that these injection distribution transformers (PH Town 106.3%, RSU 90.5%, Marine Base 86.5%, UTC 87.9%, Nzimiro 89.5%, and Borokiri 88.7%) were overloaded on the network and the operating voltages observed for (PH Town 95.1%, RSU 83.0%, Marine Base 83.4%, UTC 82.8%, Nzimiro 85.2%, and Borokiri 82.1%) indicates low voltage profile. However, using network reconfiguration technique as proposed in this paper; there was reduction in the percentage loading of the said Transformers as it was upgraded to affect positively on its lifespan with (PH Town 44.1%, RSU 65.3%, Marine Base 60.7%, UTC 47.3%, Nzimiro 61.3%, and Borokiri 52.0%) loading,  and the bus voltage profiles was improved for (PH Town 100%, RSU 98.4%, Marine Base 98.8%, UTC 98.2%, Nzimiro 98.6%, and Borokiri 99.1%) with additional facilities. It is recommended that the power infrastructure facilities in Port Harcourt Town distribution network be immediately upgraded to reduce losses and improve the electricity supply to consumers. Also, in regard to these analyses, the sub-transmission substation requires 240 MW of power for effective power delivery.

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