Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

WANG Tingling; YAN Xiaohe

doi:10.23919/cje.2022.00.024

Volume 33 Issue 1

Jan. 2024

Turn off MathJax

Article Contents

Article Navigation > Chinese Journal of Electronics > 2024 > 33(1): 264-273

Tingling WANG and Xiaohe YAN, “Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park,” Chinese Journal of Electronics, vol. 33, no. 1, pp. 264–273, 2024 doi: 10.23919/cje.2022.00.024

Citation:

Tingling WANG and Xiaohe YAN, “Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park,” Chinese Journal of Electronics, vol. 33, no. 1, pp. 264–273, 2024 doi: 10.23919/cje.2022.00.024

Citation:

PDF( 3445 KB)

Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

doi: 10.23919/cje.2022.00.024

WANG Tingling^1
,,
YAN Xiaohe^{2
,
,}

1.
School of Electric Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
2.
Wenzhou Polytechnic, Wenzhou 325035, China

More Information

Author Bio:
Tingling WANG received the M.S. degree in control science and engineering from Shaanxi University of Science and Technology. He is an Associate Professor in North China University of Water Resources and Electric Power. His research interests include wireless communication network, intelligent algorithm and detection technology. (Email: wtl@ncwu.edu.cn)

Xiaohe YAN received the M.S. degree in control engineering from Wuhan University of Technology. She is an Associate Professor in Wenzhou Polytechnic. Her research interests include wireless communication network, intelligent algorithm and automation device. (Email: xiaohewelcome@126.com)
Corresponding author: Email: xiaohewelcome@126.com
Received Date: 2022-02-23
Accepted Date: 2023-03-14

Available Online: 2023-03-22

Publish Date: 2024-01-05

Abstract

Abstract

With the rapid development of industrial parks, its load model research has become a hot spot. In order to study the load of power system in industrial park, based on the characteristics of the industrial park load, a comprehensive load admittance static model with full voltage range adaptability is considered, and a comprehensive load model of distribution network of the industrial park is established. A complete parameter identification of the model is carried out through chaos particle swarm optimization. The simulation results show that the model can effectively describe the load characteristics of the distribution network in industrial parks.
- Industrial park,
- Comprehensive load model,
- Distribution network,
- Chaos particle swarm optimization

FullText(HTML)

References(24)

References

[1]	W. W. Price, C. W. Taylor, and G. J. Rogers, “Standard load models for power flow and dynamic performance simulation,” IEEE Transactions on Power Systems, vol. 10, no. 3, pp. 1302–1313, 1995. doi: 10.1109/59.466523
[2]	Anonymous], “Bibliography on load models for power flow and dynamic performance simulation,” IEEE Transactions on Power Systems, vol. 10, no. 1, pp. 523–538, 1995. doi: 10.1109/59.373979
[3]	C. Guo, H. Xie, X. Meng, et al., “Research on parameter identification of load model based on GWO algorithm,” Journal of Electric Power Science and Technology, vol. 37, no. 2, pp. 30–37, 2022. (in Chinese) doi: 10.19781/j.issn.1673-9140.2022.02.004
[4]	X. R. Li, Y. Y. Liu, H. H. Chen, et al., “Comparative study of genetic algorithm and traditional optimization in power load modeling,” Journal of Hunan University (Natural Sciences), vol. 32, no. 2, pp. 29–32, 2005. (in Chinese) doi: 10.3321/j.issn:1000-2472.2005.02.007
[5]	P. Ju and D. F. Li, “Identification of composite induction motor loads,” Transactions of China Electrotechnical Society, vol. 14, no. 1, pp. 1–6, 1999. (in Chinese) doi: 10.3321/j.issn:1000-6753.1999.01.001
[6]	P. Ju and D. F. Li. A, “A study on the identification method of the composite electric load models,” Automation of Electric Power Systems, vol. 21, no. 8, pp. 11–14, 1997. (in Chinese)
[7]	C. Liu, Y. Y. Zhu, Q. Guo, et al., “Simplification and initialization of large-scale induction motor in real-time simulation,” Power System Technology, vol. 46, no. 1, pp. 404–411, 2022. (in Chinese) doi: 10.13335/j.1000-3673.pst.2020.2228
[8]	P. Q. Li, X. J. Zeng, J. Y. Huang, et al., “Equivalent modeling of grid-connected photovoltaic power generation systems for comprehensive load,” Automation of Electric Power Systems, vol. 40, no. 8, pp. 43–50, 2016. (in Chinese) doi: 10.7500/AEPS20150519001
[9]	X. Qu, X. R. Li, J. Y. Song, et al., “Composite load model considering voltage regulation of distribution network,” Transactions of China Electrotechnical Society, vol. 33, no. 4, pp. 759–770, 2018. (in Chinese) doi: 10.19595/j.cnki.1000-6753.tces.161431
[10]	J. M. Huang, J. Q. Zhu, and Y. C. Zhuang, “Generalized power load modeling based on dynamic RBF neural network,” Power System Technology, vol. 42, no. 2, pp. 591–597, 2018. (in Chinese) doi: 10.13335/j.1000-3673.pst.2017.1350
[11]	Y. H. Ma, “Studies on composite load modeling of distribution network considering distributed generation,” Ph. D. Thesis, Hunan University, Changsha, China, pp. 5-6, 2013. (in Chinese)
[12]	S. M. Zali and J. V. Milanović, “Generic model of active distribution network for large power system stability studies,” IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3126–3133, 2013. doi: 10.1109/TPWRS.2012.2233223
[13]	J. V. Milanović and S. M. Zali, “Validation of equivalent dynamic model of active distribution network cell,” IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2101–2110, 2013. doi: 10.1109/TPWRS.2012.2227844
[14]	X. R. Li, Y. X. Chen, and Z. Tang, “A synthetic load static model suitable for large range voltage variation,” Journal of Changsha University of Electric Power (Natural Science), vol. 14, no. 1, pp. 38–43, 1999. (in Chinese)
[15]	X. R. Li, R. M. He, and W. Zhou, “Synthetic load model suiting for voltage stability analysis,” Proceedings of the CSEE, vol. 19, no. 5, pp. 71–75, 1999. (in Chinese) doi: 10.3321/j.issn:0258-8013.1999.05.017
[16]	H. X. Li, S. Y. Li, Z. Y. Li, et al., “Online identification method of load parameters based on adaptive Kalman filter algorithm,” Electrical Automation, vol. 43, no. 4, pp. 43–45,59, 2021. (in Chinese) doi: 10.3969/j.issn.1000-3886.2021.04.012
[17]	H. J. Xie and Y. Kong, “Parameter identification of comprehensive load model based on improved chaos optimization algorithm,” Computer Programming Skills & Maintenance, no. 12, pp. 17–20,23, 2017. (in Chinese) doi: 10.16184/j.cnki.comprg.2017.12.004
[18]	D. Z. Gu, Q. Ai, C. Chen, et al., “New load models for fast transient stability calculations and parameter identification method,” Proceedings of the CSEE, vol. 24, no. 12, pp. 78–85, 2004. (in Chinese) doi: 10.13334/j.0258-8013.pcsee.2004.12.016
[19]	Y. Q. Tao and D. W. Cui, “Load identification of algorithm based on dynamic fuzzy granular neural network,” Control and Decision, vol. 26, no. 4, pp. 519–523,529, 2011. (in Chinese) doi: 10.13195/j.cd.2011.04.42.taoyq.002
[20]	X. Q. Chen, C. H. Deng, Z. D. Pan, et al., “Power system load modeling based on recurrent RBF neural network,” Power System Technology, vol. 31, no. 17, pp. 56–59, 2007. (in Chinese)
[21]	Y. Y. Du, P. Zhang, Z. J. Chen, et al., “Identification of induction motor parameters using genetic algorithm based on transfer function,” Journal of Electric Power, vol. 28, no. 1, pp. 32–34,39, 2013. (in Chinese) doi: 10.3969/j.issn.1005-6548.2013.01.008
[22]	L. Du, F. Yang, C. Wei, et al., “Parameter identification of the wide-band model of oil-impregnated paper insulation using frequency domain spectroscopy,” Transactions of China Electrotechnical Society, vol. 33, no. 5, pp. 1158–1166, 2018. (in Chinese) doi: 10.19595/j.cnki.1000-6753.tces.170043
[23]	Z. Cheng, M. N. Dong, T. L. Yang, et al., “Extraction of solar cell model parameters based on self-adaptive chaos particle swarm optimization algorithm,” Transactions of China Electrotechnical Society, vol. 29, no. 9, pp. 245–252, 2014. (in Chinese) doi: 10.3969/j.issn.1000-6753.2014.09.035
[24]	Y. M. Feng, Z. Wang, X. Y. Zhang, et al., “Parameters identification of hydro-turbine governing system based on chaos particle swarm optimization and modeling experiment,” Journal of Yangtze River Scientific Research Institute, vol. 33, no. 8, pp. 138–143, 2016. (in Chinese) doi: 10.11988/ckyyb.20150482