Multi-objective Distribution Network Dynamic Reconfiguration and DG Control Considering Time Variation of Load and DG

被引：0

作者：

Qu H. ^{[1
]}

Li X. ^{[1
]}

Yang L. ^{[1
]}

Huang Y. ^{[2
]}

Wang M. ^{[1
]}

Huang J. ^{[3
]}

机构：

[1] School of Electrical Engineering and Automation, Wuhan University, Wuhan

[2] China Electric Power Research Institute, Beijing

[3] Foshan City Power Supply Bureau of GSG, Foshan

来源：

Gaodianya Jishu/High Voltage Engineering | 2019年 / 45卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Active distribution network; Co-evolution algorithm; Dynamic reconstruction; Multi-objective optimization; Output control of distribution generation;

D O I：

10.13336/j.1003-6520.hve.20190226027

中图分类号：

学科分类号：

摘要：

In view of the dynamic demand for power load and the constantly changing upper output limit for distributed generation in distribution network, the static network reconfiguration and DG output control in a single time section can not meet the requirements of actual operation of distribution network. Consequently, we proposed a multi-objective and co-evolution model considering the time-varying characteristic of load and distributed generation output, with the index of active power loss and reconfiguration cost, voltage index and discard rate, to synchronously deal with the problems of dynamic reconstruction and regulation for distributed generation in distribution network. The CE-NSGA-II algorithm and CE-MOCLPSO algorithm were respectively designed for the problem of dynamic reconstruction and distributed generation output in distribution network. Based on the example of PG&E 69 nodes distribution network in the United States, several simulation experiments were designed for analysis. Simulation results indicate that it can effectively improve the operation level of distribution network combined with ADN dynamic reconstruction and control measures of distribution generation output, and verify the effectiveness of the proposed method. © 2019, High Voltage Engineering Editorial Department of CEPRI. All right reserved.

引用

页码：873 / 881

页数：8

共 20 条

[1]

Chen X., Jin X., Jia H., Et al., Reconfiguration strategy for active distribution network considering spatial-temporal electrical vehicle load model, High Voltage Engineering, 43, 3, pp. 1049-1056, (2017)

[2]

Yi H., Zhang B., Wang H., Et al., Distribution network dynamic reconfiguration method for improving distribution network's ability of accepting DG, Power System Technology, 40, 5, pp. 1431-1436, (2016)

[3]

Cong P., Tang W., Zhang L., Et al., Chance constrained programming based distribution network reconfiguration considering multi-states of distributed generation and load, Power System Technology, 37, 9, pp. 2573-2579, (2013)

[4]

Zhou H., Tang F., Liu D., Et al., Active distribution network dynamic reconfiguration and DG dynamic control strategy considering time-variant load, Power System Technology, 40, 8, pp. 2423-2429, (2016)

[5]

Dong R., Yang Q., Yan W., MAS-based cooperative optimization of reconfiguration in active power distribution networks, Journal of Zhejiang University(Engineering Science), 49, 19, pp. 1982-1989, (2015)

[6]

Zhao J., Niu H., Wang Y., Dynamic reconfiguration of active distribution network based on information entropy of time intervals, Power System Technology, 41, 2, pp. 402-408, (2016)

[7]

Wang C., Gao Y., Dynamic reconfiguration of distribution network based on optimal fuzzy c-means clustering and improved chemical reaction optimization, Proceedings of the CSEE, 34, 10, pp. 1682-1691, (2014)

[8]

Wang X., Wei Z., Sun G., Et al., Multi-objective distribution network reconfiguration considering uncertainties of distributed generation and load, Electric Power Automation Equipment, 36, 6, pp. 116-121, (2016)

[9]

Peng C., Yu R., Sun H., Multi-objective DG planning based on K-means clustering and multi-scenario timing characteristics analysis, Electric Power Automation Equipment, 35, 10, pp. 58-65, (2015)

[10]

Li L., Tang W., Bai M., Et al., Multi-objective locating and sizing of distributed generators based on time-sequence characteristics, Automation of Electric Power Systems, 37, 3, pp. 58-63, (2013)

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