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

Mingyi PAN; Nian LIU; Jinyong LEI

doi:10.7500/AEPS20200217013

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

Basic Research | 更新时间：2025-06-16

- Dynamic Partition Method for Distributed Energy Cluster with Combined Heat and Power Unit
- Automation of Electric Power Systems Vol. 45, Issue 1, Pages: 168-176(2021)
- 作者机构：
  
  1.新能源电力系统国家重点实验室（华北电力大学），北京市102206
  2.中国南方电网科学研究院有限责任公司，广东省广州市 510080
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China;China Southern Power Grid Company Limited
- DOI：10.7500/AEPS20200217013
  CLC：
- Received：17 February 2020，
  
  Revised：2020-09-08，
  
  Published Online：30 October 2020，
  
  Published：10 January 2021
- 稿件说明：
移动端阅览
潘明夷,刘念,雷金勇.含热电联产机组的分布式能源集群动态划分方法[J].电力系统自动化,2021,45(1):168-176.

PAN Mingyi,LIU Nian,LEI Jinyong.Dynamic Partition Method for Distributed Energy Cluster with Combined Heat and Power Unit[J].Automation of Electric Power Systems,2021,45(1):168-176.
潘明夷,刘念,雷金勇.含热电联产机组的分布式能源集群动态划分方法[J].电力系统自动化,2021,45(1):168-176. DOI： 10.7500/AEPS20200217013.

PAN Mingyi,LIU Nian,LEI Jinyong.Dynamic Partition Method for Distributed Energy Cluster with Combined Heat and Power Unit[J].Automation of Electric Power Systems,2021,45(1):168-176. DOI： 10.7500/AEPS20200217013.

摘要

集群划分是实现分布式能源网络优化调控的基础环节。文中提出含热电联产机组的分布式能源网络集群划分方法。首先，提出综合考虑结构性与功能性的集群划分指标体系：结构上采用计及电热网络特性的模块度指标，用以刻画不同网络节点间的联系强度；功能上引入供需匹配度指标和热电耦合度指标，反映单一能源网络集群内部供应和实际需求间、源侧耦合出力和实际用能间的平衡程度。其次，依托集群划分指标体系设计电网和热网2个层面的优化目标作为集群划分的依据，采用Louvain社区检测算法生成以热电联产为中心的电热双重集群。最后，通过实际算例验证了所提方法的有效性。

Abstract

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.

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references

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