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Reactive Power Optimization Approach Based on Chaotic Particle Swarm Optimization

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Advanced Machine Learning Technologies and Applications (AMLTA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1141))

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Abstract

Reactive optimization is an important measure to ensure the reliable operation of the system. In view of the characteristics of reactive optimization of power grid, a method of reactive optimization of the distribution network based on the combination of local voltage stability index partition and improved particle group algorithm is proposed. First, the local voltage stabilization index of the system load node is calculated, the load node is sorted according to the size of the voltage stabilization index, the load node is selected as the collection of candidate compensation points and the electrical distance is combined with the electrical distance to partition it, and then, the system’s optimal compensation point position and reactive compensation amount are obtained by improving the particle group algorithm. The method combined with the local voltage stabilization index and the electrical distance can narrow the range of the search, obtain the reasonable and effective candidate compensation area, improve the particle group algorithm to initialize particle diversity is better, with faster convergence speed.

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Author information

Authors and Affiliations

  1. Department of Marking, State Grid Liaoning Electric Power Supply Co. Ltd., Shenyang, 110004, China

    Fengqiang Li, Lianjun Song & Bo Cong

Authors
  1. Fengqiang Li
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  2. Lianjun Song
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  3. Bo Cong
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Corresponding author

Correspondence to Fengqiang Li .

Editor information

Editors and Affiliations

  1. Faculty of Computer and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Roheet Bhatnagar

  3. Faculty of Science, Helwan University, Helwan, Egypt

    Ashraf Darwish

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Li, F., Song, L., Cong, B. (2021). Reactive Power Optimization Approach Based on Chaotic Particle Swarm Optimization. In: Hassanien, A., Bhatnagar, R., Darwish, A. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2020. Advances in Intelligent Systems and Computing, vol 1141. Springer, Singapore. https://doi.org/10.1007/978-981-15-3383-9_12

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