A Two-Step Approach for Multi-Topology Identification and Parameter Estimation of Power Distribution Networks

Li Ma; Lei Wu; Nian Liu; Wei Pei

doi:10.17775/CSEEJPES.2021.08180

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A Two-Step Approach for Multi-Topology Identification and Parameter Estimation of Power Distribution Networks

Regular Papers | 更新时间：2026-10-15

- A Two-Step Approach for Multi-Topology Identification and Parameter Estimation of Power Distribution Networks
- CSEE Journal of Power and Energy Systems Vol. 10, Issue 6, Pages: 2446-2456(2024)
- 作者机构：
  
  1. Key Laboratory of Long-Duration and Large-Scale Energy Storage, Institute of Electrical Engineering, Chinese Academy of Sciences,Beijing,China
  2. Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken,NJ,USA
  3. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2021.08180
  CLC：
- Published：01 November 2024
- 稿件说明：
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Li Ma, Lei Wu, Nian Liu, et al. A Two-Step Approach for Multi-Topology Identification and Parameter Estimation of Power Distribution Networks[J]. CSEE Journal of Power and Energy Systems, 2024, 10(6): 2446-2456.
DOI：

Li Ma, Lei Wu, Nian Liu, et al. A Two-Step Approach for Multi-Topology Identification and Parameter Estimation of Power Distribution Networks[J]. CSEE Journal of Power and Energy Systems, 2024, 10(6): 2446-2456. DOI： 10.17775/CSEEJPES.2021.08180.

摘要

Abstract

To improve observability in power distribution networks (PDN)

a two-step framework of multi-topology identification and parameter estimation is proposed in this paper. Specifically

in the first step

a mixed-integer linear program (MILP) model-based split method is proposed to recognize mixed topologies in a multi-record dataset without a prerequisite on the number of topology categories and values of nodal voltage phase angles. In the second step

line parameters and nodal voltage phase angles are estimated using the Newton-Raphson method based on nodal measurements of real and reactive power injections

as well as voltage magnitudes. Furthermore

a modified estimation model is proposed to apply to the multi-topology dataset. Finally

case studies on an IEEE 33-bus system illustrate the effectiveness of the proposed models in identifying the PDN's topologies

as well as estimating line parameters and voltage phase angles.

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Related Institution

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