Optimal allocation of energy storage participating in peak shaving based on improved hybrid particle swarm optimization-Reference-Cited by-同舟云学术

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Optimal allocation of energy storage participating in peak shaving based on improved hybrid particle swarm optimization

Published:2023-05-12 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 6th International Electrical and Energy Conference (CIEEC)
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Author:

Zhang Ziyang¹,Jia Jiaoxin¹,Lu Junda¹,Rasool Aazim²

Affiliation:

1. North China Electric Power University,Department of Electric Engineering,BaoDing,China

2. TEMSTEC (Pvt) Ltd.,Research and Development department,Wah Cantt,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10165685/10164836/10166602.pdf?arnumber=10166602

Reference14 articles.

1. Application of improved particle swarm optimization in building energy efficiency optimization [J];gang;Journal of South China University of Technology (Natural Science Edition),2020

2. Improved localization algorithm for WSN hybrid particle swarm optimization [J];tao;Journal of Heilongjiang Institute of Technology,2020

3. Particle swarm optimization with mutation

4. Particle Swarm Optimization Algorithm Based on Asymmetric Learning Factor Adjustment [J];kaifu;Computer Engineering,2010

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1. Capacity Optimization Configuration of Aircraft Energy Storage Units Based on Particle Swarm Optimization and Neural Network Algorithm;2023 IEEE 2nd International Power Electronics and Application Symposium (PEAS);2023-11-10

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