Adaptive Particle Swarm Optimization for Reactive Power and Voltage Control in Power Systems

Author(s):  
Wen Zhang ◽  
Yutian Liu
Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5679
Author(s):  
Mohamed A. M. Shaheen ◽  
Dalia Yousri ◽  
Ahmed Fathy ◽  
Hany M. Hasanien ◽  
Abdulaziz Alkuhayli ◽  
...  

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.


2013 ◽  
Vol 846-847 ◽  
pp. 1209-1212
Author(s):  
Wen Qing Zhao ◽  
Li Wei Wang ◽  
Fei Fei Han ◽  
De Wen Wang

This paper summarizes the reactive power optimization of power system characteristics and requirements, proposed to target the active power loss of reactive power optimization mathematical model, And the traditional classical algorithm can not handle the limitations of discrete variables, using the adaptive particle swarm optimization algorithm to solve the problem of reactive power optimization. By testing on IEEE30 bus system simulation, comparing different algorithm optimization results show the effectiveness and superiority of APSO algorithm.


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