scholarly journals Optimal Network Reconfiguration to Reduce Power Loss Using an Initial Searching Point for Continuous Genetic Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen ◽  
Ngoc Au Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Closed Loop ◽  
Control Variable ◽  
Initial Population ◽  
Network Reconfiguration ◽  
Power Loss Reduction ◽  
Continuous Genetic Algorithm

In this paper, an effective method to determine an initial searching point (ISP) of the network reconfiguration (NR) problem for power loss reduction is proposed for improving the efficiency of the continuous genetic algorithm (CGA) to the NR problem. The idea of the method is to close each initial open switch in turn and solve power flow for the distribution system with the presence of a closed loop to choose a switch with the smallest current in the closed loop for opening. If the radial topology constraint of the distribution system is satisfied, the switch opened is considered as a control variable of the ISP. Then, ISP is attached to the initial population of CGA. The calculated results from the different distribution systems show that the proposed CGA using ISP could reach the optimal radial topology with better successful rate and obtained solution quality than the method based on CGA using the initial population generated randomly and the method based on CGA using the initial radial configuration attached to the initial population. As a result, CGA using ISP can be a favorable method for finding a more effective radial topology in operating distribution systems.

scholarly journals Network Reconfiguration of Primary Distribution System Using GWO Algorithm

2017 ◽  
Vol 7 (6) ◽  
pp. 3226 ◽  
Author(s):  
A. V. Sudhakara Reddy ◽  
M. Damodar Reddy ◽  
M. Satish Kumar Reddy
Keyword(s):  
Power Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Network Reconfiguration ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Real Power ◽  
Power Distribution System ◽  
Power Loss Reduction

This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfiguration problem which includes minimization of real power loss. A nature inspired Grey Wolf Optimization Algorithm is utilized to restructure the power distribution system and identify the optimal switches corresponding minimum power loss in the distribution network. The GWO technique has tested on standard IEEE 33-bus and 69-bus systems and the results are presented.

scholarly journals Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping Algorithm

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 553 ◽  
Author(s):  
Arun Onlam ◽  
Daranpob Yodphet ◽  
Rongrit Chatthaworn ◽  
Chayada Surawanitkun ◽  
Apirat Siritaratiwat ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Network Reconfiguration ◽  
Loss Minimization ◽  
Power Loss Minimization ◽  
Electrical Distribution ◽  
Power Loss Reduction

This paper proposes a novel adaptive optimization algorithm to solve the network reconfiguration and distributed generation (DG) placement problems with objective functions including power loss minimization and voltage stability index (VSI) improvement. The proposed technique called Adaptive Shuffled Frogs Leaping Algorithm (ASFLA) was performed for solving network reconfiguration and DG installation in IEEE 33- and 69-bus distribution systems with seven different scenarios. The performance of ASFLA was compared to that of other algorithms such as Fireworks Algorithm (FWA), Adaptive Cuckoo Search Algorithm (ACSA) and Shuffled Frogs Leaping Algorithm (SFLA). It was found that the power loss and VSI provided by ASFLA were better than those given by FWA, ACSA and SFLA in both 33- and 69-bus systems. The best solution of power loss reduction and VSI improvement of both 33- and 69-bus systems was achieved when the network reconfiguration with optimal sizing and the location DG were simultaneously implemented. From our analysis, it was indicated that the ASFLA could provide better solutions than other methods since the generating process, local and global searching of this algorithm were significantly improved from a conventional method. Hence, the ASFLA becomes another effective algorithm for solving network reconfiguration and DG placement problems in electrical distribution systems.

scholarly journals RECONFIGURATION OF DISTRIBUTION SYSTEMS FOR LOSS REDUCTION USING A GENETIC ALGORITHM

2012 ◽  
Vol 15 (2) ◽  
pp. 17-26
Author(s):  
Loc Dac Ho
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Distribution System ◽  
Power Loss ◽  
Power Plants ◽  
Distribution Systems ◽  
Optimal Configuration ◽  
Loss Reduction ◽  
Voltage Drops ◽  
Simulation Results

A distribution system is one of the most important parts of power systems which show a connection between power plants and loads. Each connection has an economic affection in transferring power from sources to loads. Power companies expect to find out an optimal configuration with great benefits which is the lowest power loss. This paper proposes an application of a genetic algorithm for finding out an optimal configuration which has the lowest power loss with constrains such as: unisolated loads, limited powers in lines and transformers and lowest voltage drops. The effectiveness of the proposal is confirmed through simulation results on power systems [3] as well as comparisons with other results of [1], [3], [6], [8]

scholarly journals Recloser-Fuse settings in distribution systems with optimizing multiple distributed generation considering technical aspects

2020 ◽  
Vol 17 (3) ◽  
pp. 1135
Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Test System ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
System Power

<p><span>With the widespread of using distributed generation, the connection of DGs in the distribution system causes miscoordination between protective devices. This paper introduces the problems associated with recloser fuse miscoordination (RFM) in the presence of single and multiple DG in a radial distribution system. Two Multi objective optimization problems are presented. The first is based on technical impacts to determine the optimal size and location of DG considering system power loss reduction and enhancement the voltage profile with a certain constraints and the second is used for minimizing the operating time of all fuses and recloser with obtaining the optimum settings of fuse recloser coordination characteristics. Whale Optimizer algorithm (WOA) emulated RFM as an optimization problem. The performance of the proposed methodology is applied to the standard IEEE 33 node test system. The results show the robustness of the proposed algorithm for solving the RFM problem with achieving system power loss reduction and voltage profile enhancement.</span></p>

scholarly journals Multi-Objective Planning for Optimal Allocation of DG and RPC Units in Radial Distribution System Using Genetic Algorithm

10.29007/bngk ◽  
2018 ◽  
Author(s):  
Jaydeepsinh Sarvaiya ◽  
Mahipalsinh Chudasama
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Network ◽  
Cost Effective ◽  
Loss Reduction ◽  
Effective Solution ◽  
Radial Distribution System ◽  
Real Power ◽  
Power Loss Reduction

DG penetration is continuously increased across distribution network not only to reduce carbon emission, but also to enhance the performance of the distribution network. In a restructured environment any distribution utility need to address DG placement and sizing problem to find a cost effective solution for the specific investment. Most of the authors have attempted to solve the problem based on real power loss reduction across the network. Some authors consider voltage stability based analysis for increased loadability of network with real power loss. However, optimal reactive power compensation also need to be incorporated for a cost effective solution. In this paper an attempt has been made to address various types of DG and RPC units citing and sizing problem with multi-objectives consists real power loss reduction and VSI improvement. A new approach includes development of cost function to find cost-effective solution for distribution network. Evolutionary based Genetic Algorithm used to optimize the objective function. Proposed algorithm is tested onIEEE-33 bus radial distribution system.

scholarly journals Energy Loss Minimization by Optimal Siting and Sizing of DG with Network Reconfiguration in Distribution Networks

2019 ◽  
Vol 8 (10) ◽  
pp. 3621-3625
Keyword(s):  
Energy Loss ◽  
Distribution System ◽  
Power Loss ◽  
Reactive Power ◽  
Low Voltage ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Loss Minimization ◽  
Power Loss Reduction

The main aim of the distribution system is delivery the power to the consumers. Because of, aging of electrical infrastructure, old control mechanism, increased power demand causing exploitation of the present electrical networks leads to low voltage profile, more active and reactive power loss with various power quality related issues causing poor network operation. In this method maximization of voltage profile with energy loss minimization is carried using network reconfiguration along with optimal siting of the distributed generation (DG). The proposed methodology is carried out on five bus system. The obtained results are impressive interms of voltage stability and power loss reduction.

Study on Implementation Strategy of Network Reconfiguration in Distribution System

2012 ◽  
Vol 614-615 ◽  
pp. 976-979
Author(s):  
Bin Zheng Dong ◽  
Bao Zhu Liu ◽  
Guo Liang Guo ◽  
Yun Xiao Bai
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Implementation Strategy ◽  
Closed Loop ◽  
Network Reconfiguration ◽  
Loop Current ◽  
System Reconfiguration ◽  
Operation Sequence ◽  
Switch Operation ◽  
Distribution System Reconfiguration

Distribution system reconfiguration is the main measure to optimize the distribution system, which can dramatically lower the power loss of the network. This paper deals with the switch operation sequence considering closed-loop current constraints and puts forward the concept of “switch compounding”. A new implementation strategy is proposed to realize a feasible operation sequence. The strategy is tested on IEEE33 system, which verifies the effectiveness of the strategy.

scholarly journals Optimal electric distribution network configuration using adaptive sunflower optimization

2021 ◽  
Vol 10 (4) ◽  
pp. 1777-1784
Author(s):  
Thuan Thanh Nguyen ◽  
Ngoc Thiem Nguyen ◽  
Trung Dung Nguyen
Keyword(s):  
Distribution System ◽  
Power Loss ◽  
Network Reconfiguration ◽  
Network Configuration ◽  
Solution Quality ◽  
Electric Distribution Network ◽  
Optimal Network ◽  
Comparison Results ◽  
Power Loss Reduction ◽  
Powerful Approach

Network reconfiguration (NR) is a powerful approach for power loss reduction in the distribution system. This paper presents a method of network reconfiguration using adaptive sunflower optimization (ASFO) to minimize power loss of the distribution system. ASFO is developed based on the original sunflower optimization (SFO) that is inspired from moving of sunflower to the sun. In ASFO, the mechanisms including pollination, survival and mortality mechanisms have been adjusted compared to the original SFO to fit with the network reconfiguration problem. The numerical results on the 14-node and 33-node systems have shown that ASFO outperforms to SFO for finding the optimal network configuration with greater success rate and better obtained solution quality. The comparison results with other previous approaches also indicate that ASFO has better performance than other methods in term of optimal network configuration. Thus, ASFO is a powerful method for the NR.

scholarly journals Power Loss Reduction using Instantaneous Network Reconfiguration and DG Placement with Cuckoo Search Algorithm in Distribution System

2020 ◽  
Vol 8 (6) ◽  
pp. 2393-2398
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Power Loss ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Network Reconfiguration ◽  
Radial Distribution System ◽  
Distributed Generator ◽  
Power Loss Reduction

The aim of reducing power loss, enhancing profile of voltage in a radial distribution system at which consumers are connected and also determining the ratings of power, optimal placement of Distributed generator. In this paper to resolve the drop in voltage profile by using network reconfiguration that gives possible switching possibilities with an efficient Cuckoo Search Algorithm (CSA) is discussed and Sensitivity analysis are carried out simultaneously for finding sizing and possible location of distributed generation. To confirm the usefulness of the discussed method it was conducted on radial distribution system of 33 bus connected by various load levels, the result shows that the discussed method is fast and efficient. However to meet power requirement and lack of transmission capabilities importance for DG is rapidly evolving in electrical systems. For reliability and stability for the power system best possible location of Distributed Generator is needed in distribution system. To overcome the shortcomings of mathematical optimization practices, soft computing algorithms have been actively introduced during the last decade.

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