A novel metaheuristic method based on artificial ecosystem-based optimization for optimization of network reconfiguration to reduce power loss

2021 ◽  
Author(s):  
Thuan Thanh Nguyen
Keyword(s):  
Power Loss ◽  
Network Reconfiguration ◽  
Artificial Ecosystem

scholarly journals Symbiotic Organism Search Algorithm for Power Loss Minimization in Radial Distribution Systems by Network Reconfiguration and Distributed Generation Placement

2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Tung Tran The ◽  
Sy Nguyen Quoc ◽  
Dieu Vo Ngoc
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Power Loss ◽  
Distribution Systems ◽  
Large Scale ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Distribution Networks ◽  
Network Reconfiguration ◽  
Symbiotic Organism Search

This paper proposes the Symbiotic Organism Search (SOS) algorithm to find the optimal network configuration and the placement of distributed generation (DG) units that minimize the real power loss in radial distribution networks. The proposed algorithm simulates symbiotic relationships such as mutualism, commensalism, and parasitism for solving the optimization problems. In the optimization process, the reconfiguration problem produces a large number of infeasible network configurations. To reduce these infeasible individuals and ensure the radial topology of the network, the graph theory was applied during the power flow. The implementation of the proposed SOS algorithm was carried out on 33-bus, 69-bus, 84-bus, and 119-bus distribution networks considering seven different scenarios. Simulation results and performance comparison with other optimization methods showed that the SOS-based approach was very effective in solving the network reconfiguration and DG placement problems, especially for complex and large-scale distribution networks.

A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array

2020 ◽  
Vol 225 ◽  
pp. 113385 ◽  
Author(s):  
Dalia Yousri ◽  
Thanikanti Sudhakar Babu ◽  
Seyedali Mirjalili ◽  
N. Rajasekar ◽  
Mohamed Abd Elaziz
Keyword(s):  
Objective Function ◽  
Power Loss ◽  
Large Scale ◽  
Photovoltaic Array ◽  
Artificial Ecosystem

scholarly journals OPTIMASI PENEMPATAN KAPASITOR BANK UNTUK PERBAIKAN RUGI DAYA PADA PENYULANG SABA MENGGUNAKAN ALGORITMA GENETIKA

2019 ◽  
Vol 6 (2) ◽  
pp. 7
Author(s):  
I. K. A. Wijaya ◽  
R. S. Hartati ◽  
I W. Sukerayasa
Keyword(s):  
Genetic Algorithms ◽  
Power Loss ◽  
Voltage Drop ◽  
Electrical Energy ◽  
Total Power ◽  
Network Reconfiguration ◽  
Power Losses ◽  
Combined Method ◽  
Capacitor Banks ◽  
Distribution Transformers

Saba feeder is a feeder who supplies 78 distribution transformers with feeder length 38,959 kms, through this Saba feeder electrical energy is channeled radially to each distribution substation. In 2017 the voltage shrinkage at Saba feeder was 9.88% (18,024 kV) while the total power loss was 445.5 kW. In this study an attempt was made to overcome the voltage losses and power losses using the method of optimizing bank capacitors with genetic algorithms and network reconfiguration. The best solution obtained from this study will be selected for repair of voltage losses and power losses in Saba feeders. The results showed that by optimizing bank capacitors using genetic algorithms, the placement of capacitor banks was placed on bus 23 (the channel leading to the BB0024 transformer) and successfully reduced the power loss to 331.7 kW. The network reconfiguration succeeded in fixing the voltage on the Saba feeder with a voltage drop of 4.75% and a total power loss of 182.7 kW. With the combined method, reconfiguration and optimization of bank capacitors with genetic algorithms were obtained on bus 27 (channel to transformer BB0047) and managed to reduce power losses to 143 kW.

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.

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