Distributed generator planning method in distribution network based on clustering network topology and source-load correlation scenarios

被引：0

作者：

Wang Y. ^{[1
]}

Xiang Y. ^{[1
]}

Liu J. ^{[1
]}

机构：

[1] College of Electrical Engineering, Sichuan University, Chengdu

来源：

Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2020年 / 40卷 / 12期

基金：

中国国家自然科学基金;

关键词：

Clustering algorithm; Correlation; Distributed power generation; Distribution network; Planning; SimRank++ algorithm; Typical network topology; Typical scenario;

D O I：

10.16081/j.epae.202010019

中图分类号：

学科分类号：

摘要：

Under the diversified distribution network topology structure, a distributed generator planning method in distribution network based on clustering network topology is proposed, which could estimate the cost of incentives for distributed generator planning quickly and effectively. Meanwhile, the correlation between load and distributed generator is fully considered in the planning stage, and the source-load correlation scenario planning method based on Copula theory is proposed. Firstly, by using SimRank++ algorithm to calculate the similarity between different feeder topologies, the hierarchical clustering algorithm is used to obtain different feeder clusters of distribution network, and the cluster centers are taken as typical network topologies. According to each typical network topology, a distributed generator planning model is established with the goal of economy, and the model is optimized by simulated annealing particle swarm optimization algorithm. The analysis of the actual urban distribution network shows that the method can guide the planning of distributed generator flexibly under the diversified network, which could provide a reference basis for the strategic planning of renewable energy sources and distribution network. © 2020, Electric Power Automation Equipment Press. All right reserved.

引用

页码：49 / 56and65

页数：5616

共 23 条

[1]

(2019)

[2]

LEVI V, STRBAC G, ALLAN R., Assessment of performance-driven investment strategies of distribution systems using reference networks, IEE Proceedings-Generation, Transmis-sion and Distribution, 152, 1, pp. 1-10, (2005)

[3]

ZHANG Shenxi, YUAN Jiayan, CHENG Haozhong, Et al., Optimal distributed generation planning in active distribution network considering demand side management and network reconfiguration, Proceedings of the CSEE, 36, 1, pp. 1-9, (2016)

[4]

SU Haifeing, HU Mengjin, LIANG Zhirui, Distributed generation & energy stroage planning based on timing characteristics, Electric Power Automation Equipment, 36, 6, pp. 56-63, (2016)

[5]

ZHANG Shenxi, LI Ke, CHENG Haozhong, Optimal allocation of intermittent distributed generator in active distribution network, Electric Power Automation Equipment, 35, 11, pp. 45-51, (2015)

[6]

SUN Huijuan, LIU Jun, PENG Chunhua, Multi-objective DG planning based on classified probability integration multi-scenario analysis, Electric Power Automation Equipment, 38, 12, pp. 39-45, (2018)

[7]

JAIN N, SINGH S N, SRIVASTAVA S C., A generalized approach for DG planning and viability analysis under market scenario, IEEE Transactions on Industrial Electronics, 60, 11, pp. 5075-5085, (2013)

[8]

GAO Yiwen, LIU Junyong, LEI Cheng, Et al., DG planning considering the variation of the distribution network structure, Power System Protection and Control, 42, 4, pp. 40-46, (2014)

[9]

BABU P V, SINGH S P., Optimal placement of DG in dis-tribution network for power loss minimization using NLP & PLS technique, Energy Procedia, 90, pp. 441-454, (2016)

[10]

XU Rui, LIU Junyong, LIU Youbo, Et al., Primary and subordinate distribution network planning considering load clustering partition and DG integration, Electric Power Automation Equipment, 36, 6, pp. 48-55, (2016)

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