Login Register Cart 0
Generic placeholder image

Recent Advances in Electrical & Electronic Engineering

Editor-in-Chief

ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Voltage Regulation Strategy of Distribution Network with Decentralized Wind Power Based on Cluster Partition

Author(s): Shi Su, Jinyong Lei, Yuting Yan, Shuhui Pan, Yang Yang, Hao Bai, Wei Li*, Jun Chen and Qindao Zhao

Volume 16, Issue 1, 2023

Published on: 04 October, 2022

Page: [30 - 44] Pages: 15

DOI: 10.2174/2352096515666220902125455

Price: $65

Abstract

Background: With the access to large-scale distributed energy, the voltage off-limit problem of the distribution network has become more and more serious, and the traditional centralized voltage control method has been difficult to meet the demand of distribution network control and market development.

Methods: In this paper, a voltage regulation strategy based on decentralized wind power clustering is proposed. Considering the active and reactive power regulation ability of decentralized wind power, based on the cluster division of distributed energy, the goal is to minimize power regulation and voltage fluctuation within the cluster. Combining the K-means clustering algorithm and optimized PSO algorithm for voltage regulation within the cluster ensures that the voltagecrossing problem is solved. After the voltage regulation of all clusters, the auxiliary service transaction of voltage regulation is implemented to complete the voltage regulation of the whole network.

Results: Taking ieee33 bus system as an example, the MATLAB simulation shows that the decentralized wind power access triggered voltage overrun. Using the proposed cluster division method to cluster the model, the clustered voltage regulation of the nodes with voltage overrun or reaching the limit resulted in greater voltage down-regulation than the overall voltage regulation.

Conclusion: The proposed voltage regulation strategy has better advantages. It is verified that the proposed voltage regulation strategy not only solves the voltage overrun problem, but also reduces voltage fluctuations and the amount of power regulation used for voltage regulation, increasing the utilization of distributed energy with better superiority.

Keywords: Voltage regulation, cluster division, decentralized wind power, PSO algorithm, K-means clustering, algorithm.

« Previous Next »
Graphical Abstract

[1]
The Central Committee of the Communist Party of China and State Council, "Several opinions on further deepening the reform of the electric power system", Sci. Res, vol. 2, no. 9, 2015.
[2]
National Development and Reform Commission, National Energy Administration, Notice on launching pilot projects for marketoriented distributed power generation transactions ([2017] No.1901)[R], 2017.
[3]
K. Shi, L. Nian, J. Zhang, and J. Lei, "Random matching trading mechanism in microgrid of multi-operators", Power Sys. Technol., vol. 40, no. 2, pp. 587-594, 2016.
[4]
J. Lee, J. Guo, J.K. Choi, and M. Zukerman, "Distributed energy trading in microgrids: A game-theoretic model and its equilibrium analysis", IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 3524-3533, 2015.
[http://dx.doi.org/10.1109/TIE.2014.2387340]
[5]
H. Huang, S. Nie, J. Lin, Y. Wang, and J. Dong, "Optimization of peer-to-peer power trading in a microgrid with distributed PV and battery energy storage systems", Sustainability, vol. 12, no. 3, p. 9S23, 2020.
[http://dx.doi.org/10.3390/su12030923]
[6]
C. Zhang, J. Wu, Y. Zhou, M. Cheng, and S C. Long, "Peer-to-Peer energy trading in a Microgrid", Appl. Energy, vol. 220, pp. 1-12, 2018.
[http://dx.doi.org/10.1016/j.apenergy.2018.03.010]
[7]
L. Nian, X. Yu, W. Cheng, and J. Wang, "Energy sharing management for microgrids with PV prosumers: A stackelberg game approach", IEEE Trans. Industr. Inform., vol. 13, no. 3, pp. 1088-1098, 2017.
[http://dx.doi.org/10.1109/TII.2017.2654302]
[8]
K. Karimizadeh, S. Soleymani, and F. Faghihi, "Microgrid utilization by optimal allocation of DG units: Game theory coalition formulation strategy and uncertainty in renewable energy resources", J. Renew. Sustain. Energy, vol. 11, no. 2, p. 025505, 2019.
[http://dx.doi.org/10.1063/1.5078720]
[9]
L. Ma, N. Liu, J. Zhang, W. Tushar, and C. Yuen, "Energy management for joint operation of CHP and PV prosumers inside a grid-connected microgrid: A game theoretic approach", IEEE Trans. Industr. Inform., vol. 12, no. 5, pp. 1930-1942, 2016.
[http://dx.doi.org/10.1109/TII.2016.2578184]
[10]
N. Liu, L. He, X. Yu, L. Ma, Yu. Xinghuo, and Ma. Li, "Multiparty energy management for grid-connected microgrids with heat- and electricity-coupled demand response. IEEE Trans", IEEE Trans. Industr. Inform., vol. 14, no. 5, pp. 1887-1897, 2018.
[http://dx.doi.org/10.1109/TII.2017.2757443]
[11]
Z. Liu, R. Liu, L. Ning, and X. Liu, "Energy trading method of multi-microgrids based on game theory", Power Sys. Technol., vol. 45, no. 2, pp. 587-595, 2021.
[12]
L. Yu, M. Chen, F. Yang, and X. Liu, "A fuzzy control strategy for pumped storage system of the microgrid with wind power", Recent Adv. Electr. Electron. Eng., vol. 7, no. 1, pp. 37-46, 2014.
[http://dx.doi.org/10.2174/2213111607666140516234304]
[13]
Zhongguan Wang, Leijiao Ge, Jinjin Ding, and Weide Gu, "Distributed newton-based voltage control method for high-penetration PV generation cluster in active distribution networks", Renew. Power Gener., vol. 14, no. 11, pp. 1904-1911, 2020.
[http://dx.doi.org/10.1049/iet-rpg.2020.0163]
[14]
Giuseppe Fusco, and Mario Russo, "A decentralized approach for voltage control by multiple distributed energy resources", Energy Intel. Distri. Energy Sol., vol. 12, no. 4, pp. 3115-27, 2021.
[http://dx.doi.org/10.1109/TSG.2021.3057546]
[15]
X. Zhang, R. Zhang, J. Wang, and L. Wang, "An adaptive particle swarm optimization algorithm based on aggregation degree", Recent Adv. Electr. Electron. Eng., vol. 11, no. 4, pp. 443-448, 2018.
[http://dx.doi.org/10.2174/2352096511666180214125027]
[16]
L.I. Guowu, L.I. Yanqiong, and L.I.U. Jiaoyang, "Planning method for capacity of distributed energy storage considering cluster partition", Adv. Aspects Comput. Intel. App. Fuzzy Logic Soft Comput., vol. 30, no. 12, pp. 1-10, 2018.
[17]
S. Younes, K. Houshang, and M. Filippo, "Coordinated control of distributed energy resources using features of voltage disturbances", IEEE Xxplore, vol. 16, no. 6, pp. 3895-3904, 2020.
[18]
J. Dai, P. Chang, X. Zhou, Y. Tang, and Y. Li, "Optimal dispatching of power system by introducing concentrating solar power station to promote large-scale wind power and photovoltaic accommodation", Recent Adv. Electr. Electron. Eng., vol. 14, no. 4, pp. 484-492, 2021.
[http://dx.doi.org/10.2174/2352096513666201104161830]
[19]
Y. Chai, L. Guo, C. Wang, Z. Zhao, X. Du, and J. Pan, "Network partition and voltage coordination control for distribution networks with high penetration of distributed PV units", IEEE Trans. Power Syst., vol. 33, no. 3, pp. 3396-3407, 2018.
[http://dx.doi.org/10.1109/TPWRS.2018.2813400]
[20]
J. Guo, G. Hug, and O.K. Tonguz, "Intelligent partitioning in distributed optimization of electric power systems", IEEE Trans. Smart Grid, vol. 7, no. 3, pp. 1249-1258, 2016.
[http://dx.doi.org/10.1109/TSG.2015.2490553]
[21]
B. Zhao, Z. Xu, C. Xu, C. Wang, and F. Lin, "Network partition-based zonal voltage control for distribution networks with distributed PV systems", IEEE Trans. Smart Grid, vol. 9, no. 5, pp. 4087-4098, 2018.
[http://dx.doi.org/10.1109/TSG.2017.2648779]
[22]
C. Wei, Z. Md, Fadlullah Kato. Nei, and Takeuchi. Akira, "GT-CFS: A game theoretic coalition formulation strategy for reducing power loss in micro grids", IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 9, pp. 2307-2317, 2014.
[http://dx.doi.org/10.1109/TPDS.2013.178]
[23]
W. Saad, Z. Han, and H.V. Poor, "Coalitional game theory for cooperative micro-grid distribution networks", IEEE International Conference on Communications Workshops, 5 Jun – 9 Jun, 2011, Kyoto, Japan, pp. 1-5, 2011.
[http://dx.doi.org/10.1109/iccw.2011.5963577]
[24]
Manuel V. Castro, Carlos Moreira, and Leonel M. Carvalho, "Hierarchical optimisation strategy for energy scheduling and volt/var control in autonomous clusters of microgrids", vol. 14, no. 1, pp. 27-38, 2019.
[25]
Sudipta Ghosh, Younes J. Isbeih, Rojan Bhattarai, Mohamed Shawky El Moursi, Ehab F. El-Saadany, and Sukumar Kamalasadan, "A dynamic coordination control architecture for reactive power capability enhancement of the dfig-based wind power generation", vol. 35, no. 4, pp. 3051-64, 2020.
[http://dx.doi.org/10.1109/TPWRS.2020.2968483]
[26]
Hugang Xiong, Haozhong Cheng, and Kong Tao, "Network partitioning for reactive power/voltage control based on immune-central point clustering algorithm", Research Gate, vol. 31, no. 2, pp. 22-26, 2007.
[27]
Reham A. Osama, Ahmed F. Zobaa, and Almoataz Y. Abdelaziz, "A planning framework for optimal partitioning of distribution networks into microgrids", IEEE Xplore, vol. 14, no. 1, pp. 916-926, 2020.
[http://dx.doi.org/10.1109/JSYST.2019.2904319]
[28]
S. Saleem, I.L. Animasaun, S.J. Yook, Q.M. Al-Mdallal, N.A. Shah, and M. Faisal, "Insight into the motion of water conveying three kinds of nanoparticles shapes on a horizontal surface: Significance of thermo-migration and Brownian motion", Surf. Interfaces, vol. 30, p. 101854, 2022.
[http://dx.doi.org/10.1016/j.surfin.2022.101854]

Rights & Permissions Print Cite
Article Metrics
1
© 2024 Bentham Science Publishers | Privacy Policy