Probabilistic analysis of wind turbine planning using continuous genetic algorithm in distribution systems

2014 ◽  
Author(s):  
Mahmood Sadeghi ◽  
Mohsen Kalantar
Keyword(s):  
Genetic Algorithm ◽  
Wind Turbine ◽  
Probabilistic Analysis ◽  
Distribution Systems ◽  
Continuous Genetic Algorithm

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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