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 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 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.

scholarly journals Finding Radial Network Configuration of Distribution System Based on Modified Symbiotic Organisms Search

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-23
Author(s):  
Thuan Thanh Nguyen ◽  
Thanh-Quyen Ngo ◽  
Thanh Long Duong ◽  
Thang Trung Nguyen
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Network Reconfiguration ◽  
Success Rates ◽  
Network Configuration ◽  
Symbiotic Organisms Search ◽  
Comparison Results ◽  
Symbiotic Organisms ◽  
Radial Network

Network reconfiguration (NR) is one of the most effective methods to reduce line power loss in the distribution system, which causes higher losses than the other parts of the power system. This paper proposes a modified symbiotic organisms search (MSOS) algorithm to solve the NR problem. For the purpose of enhancing the effectiveness of MSOS, the mutualism and parasitism strategies of the original symbiotic organisms search (SOS) have been modified to create better new solutions. In the mutualism strategy, the so-far best solution is updated immediately as soon as new solutions are created. In the parasitism strategy, the update is only implemented for the first half of control variables, whereas another half still remains unchanged. The comparison results between MSOS and SOS on twenty-five benchmark functions and different scales of test distribution systems with 14, 33, 69, and 119 nodes show that the improvement level of MSOS over SOS is significant with higher success rates and better quality of gained solutions. Similarly, MSOS also reaches better results than other methods in the literature. Consequently, MSOS can be a favorable method for determining the most appropriate configurations for the distribution systems.

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.

scholarly journals Optimal Reconfiguration of Distribution Network in Presence of D-STATCOM and Photovoltaic Array using a Metaheuristic Algorithm

2020 ◽  
Vol 4 (5) ◽  
Author(s):  
Kola Sampangi Sambaiah ◽  
T. Jayabarathi
Keyword(s):  
Optimization Algorithm ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Flower Pollination Algorithm ◽  
Network Reconfiguration ◽  
Voltage Profile ◽  
Photovoltaic Array ◽  
Optimal Network ◽  
Grasshopper Optimization Algorithm

In this paper, grasshopper optimization algorithm (GOA) a novel meta-heuristic optimization algorithm is used to solve the network reconfiguration problem in presence of distribution static compensator (D-STATCOM) and photovoltaic (PV) arrays in a distribution system. Here, D-STATCOM acts as distribution flexible ac transmission (D-FACT) device and PV arrays as decentralized or distributed generation (DG). The main purpose of the present research includes power loss minimization and voltage profile (VP) enhancement in radial distribution systems under different loading conditions. The proposed GOA is based on swarming behavior of grasshoppers in nature. The proposed GOA is validated using the standard 33, 69 and 118 – bus test systems. The simulation results proved that the optimal network reconfiguration in presence of D-STATCOM units and PV arrays leads to significant reduction in power loss and enhancement in VP. The results obtained by the proposed GOA are compared with base value and found that the optimal network reconfiguration in presence of D-STATCOM and PV arrays is more beneficial than individual objective optimization. Also, the proposed GOA is more accurate, efficient and reliable in finding optimal solution when compared to existing modified flower pollination algorithm (MFPA), firework algorithm (FWA), fuzzy-based ant colony optimization (ACO) and genetic algorithm (GA).

scholarly journals Electric distribution network reconfiguration for power loss reduction based on runner root algorithm

2020 ◽  
Vol 10 (5) ◽  
pp. 5016
Author(s):  
Thuan Thanh Nguyen
Keyword(s):  
Power Loss ◽  
Distribution Network ◽  
Optimal Solution ◽  
Potential Method ◽  
Network Reconfiguration ◽  
Distribution Network Reconfiguration ◽  
Electric Distribution Network ◽  
Power Loss Reduction ◽  
Random Jumps ◽  
Elite Selection

This paper proposes a method for solving the distribution network reconfiguration (NR) problem based on runner root algorithm (RRA) for reducing active power loss. The RRA is a recent developed metaheuristic algorithm inspired from runners and roots of plants to search water and minerals. RRA is equipped with four tools for searching the optimal solution. In which, the random jumps and the restart of population are used for exploring and the elite selection and random jumps around the current best solution are used for exploiting. The effectiveness of the RRA is evaluated on the 16 and 69-node system. The obtained results are compared with particle swarm optimization and other methods. The numerical results show that the RRA is the potential method for the NR problem.

Sign in / Sign up

Export Citation Format

Share Document