Reactive Power Optimization Algorithm of Particle Swarm Optimization with Sensitivity Analysis

2013 ◽  
Vol 811 ◽  
pp. 666-671
Author(s):  
Yan Wen Liu ◽  
Ke Yin Jia ◽  
Hao Wang ◽  
Yan Hua Wang

Reactive power optimization is very important to power systems economic operation and nowadays, the research about it gets more and more popular. The paper presents a reactive power optimization algorithm of particle swarm optimization combined with sensitivity analysis. The paper first builds the mathematic model of reactive power optimization and introduces particle swarm optimization. Then, presents the sensitivity method in detail and talks about the process of computing the sensitivity. Finally, take the algorithm into practical application and the results proves that sensitivity analysis could improve the particle swarm optimization algorithm.

2014 ◽  
Vol 494-495 ◽  
pp. 1857-1860
Author(s):  
Ying Ai ◽  
Hong Wei Nie ◽  
Yi Xin Su ◽  
Dan Hong Zhang ◽  
Yao Peng

In order to reduce the active network loss, increase the power quality and voltage static stability of power system, an index function of multi-objective reactive power optimization is established. Then, an improved adaptive chaotic particle swarm optimization algorithm is proposed to solve the problem. Through the using of cubic chaotic mapping, the particle population is initialized to enhance the diversity of its value; In the optimization process, poor fitness particles are updated with chaos disturbance, and their inertia weight are adjusted dynamically with particles fitness value so as to avoid local convergence. Simulation of IEEE 30 bus system shows that the proposed algorithm for reactive power optimization can avoid premature convergence effectively, and converge to optimal solution rapidly.


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