Dynamic Partition Method for Distributed Energy Cluster with Combined Heat and Power Unit

被引：0
|
作者：
Pan M. [1 ]
Liu N. [1 ]
Lei J. [2 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Beijing
[2] Electric Power Research Institute of China Southern Power Grid Company Limited, Guangzhou
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2021年 / 45卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Cluster partition; Combined heat and power unit; Community detection algorithm; Distributed energy resource;
D O I：
10.7500/AEPS20200217013
中图分类号：
学科分类号：
摘要：
The cluster partition is the basic part of realizing the optimal dispatching of distributed energy networks. A cluster partition method for distributed energy networks with combined heat and power unit is proposed in this paper. Firstly, a cluster partition index system considering the structural and functional properties is proposed. The modular index that takes into account the characteristics of electric and heat network is used on the structural property to describe the connection strength between different network nodes. On the functional property, the indices of supply-demand matching degree and heat-electricity coupling degree are introduced to reflect the balance degree between the internal supply and actual demand as well as source-side coupling output and actual consumption in a single energy network cluster. Secondly, based on the cluster partition index system, the optimization objectives at the two levels of the power grid and heat network are designed as the basis for cluster partition. Thus, an electricity-heat cluster centered on combined heat and power generation is formed by Louvain community detection algorithm. Finally, the effectiveness of the proposed method is verified through the case study. © 2021 Automation of Electric Power Systems Press.
引用
收藏
页码：168 / 176
页数：8
相关论文
共 24 条
  • [1] LIU Nian, WANG Jie, WANG Lingfeng, Hybrid energy sharing for multiple microgrids in an integrated heat-electricity energy system, IEEE Transactions on Sustainable Energy, 10, 13, pp. 1139-1151, (2019)
  • [2] WU Wenchuan, ZHANG Boming, SUN Hongbin, Et al., Energy management and distributed energy resources cluster control for active distribution networks, Automation of Electric Power Systems, 44, 9, pp. 111-120, (2020)
  • [3] LEKSAWAT S, SCHMELTER A, ORTJOHANN E, Et al., Demonstration of cluster-based power system automation for future smart grids, IEEE International Energy Conference, pp. 1-6, (2016)
  • [4] NAYERIPOUR M, FALLAHZADEH-ABARGHOUEI H, WAFFENSCHMIDT E, Et al., Coordinated online voltage management of distributed generation using network partitioning, Electric Power Systems Research, 141, pp. 202-209, (2016)
  • [5] WEI C, FADLULLAH Z M, KATO N, Et al., GT-CFS: a game theoretic coalition formulation strategy for reducing power loss in microgrids, IEEE Transactions on Parallel and Distributed Systems, 25, 9, pp. 2307-2317, (2014)
  • [6] ZHANG Xu, CHEN Yunlong, WANG Yixian, Et al., Reactive power-voltage partitioning of power grid with wind power based on correction of power flow section, Electric Power Automation Equipment, 39, 10, pp. 48-54, (2019)
  • [7] DING Ming, LIU Xianfang, BI Rui, Et al., Method for cluster partition of high-penetration distributed generators based on comprehensive performance index, Automation of Electric Power Systems, 42, 15, pp. 47-52, (2018)
  • [8] LI Guowu, LI Yanqiong, LIU Jiaoyang, Et al., Planning method for capacity of distributed energy storage considering cluster partition, Proceedings of the CSU-EPSA, 30, 12, pp. 1-10, (2018)
  • [9] ZHAO Chuanzhi, ZHAO Jintang, WU Chunchao, Et al., Power grid partitioning based on functional community structure, IEEE Access, 7, pp. 152624-152634, (2019)
  • [10] YU Lin, SUN Ying, XU Ran, Et al., Improved particle swarm optimization algorithm and its application in reactive power partitioning of power grid, Automation of Electric Power Systems, 41, 3, pp. 89-95, (2017)
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