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Topology Consistency Verification in Power System Based on Data Inference

  • Zixu Wei
  • , Xiaoshu Yuan
  • , Zijun Wang
  • , Tong Zhang
  • , Zhiyi Xing
  • , Yang Liu
  • , Yadong Zhou
  • , Ting Liu
  • Xi'an Jiaotong University
  • Energy Equipment Cyber Security Key Laboratory of Sichuan Province
  • Chinese Academy of Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In recent years, with the development of the Internet of Things (IoT) and the deepening of marketization, more and more industries related to the power system require necessary information disclosure. However, there is often inconsistency between the publicly available data of the power system and the actual operational electricity transaction data, and the publicly available data from different sources also do not match. This paper proposes a data inference-based method for verifying the consistency between electricity price data and publicly available topology, aiming to address the issue of data inconsistency in real scenarios. This method achieves the consistency verification between electricity market prices and publicly available topology through steps such as data collection and preprocessing, power system model construction, and topology consistency verification. This paper conducts a comprehensive study on the publicly available electricity price data and the power grid model, and constructs the physical coupling relationship of the data under the power optimization model. Furthermore, the effectiveness of the data inference-based method for verifying the consistency between electricity market prices and publicly available topology is validated through experiments conducted on a real data constructed power grid case.

Original languageEnglish
Title of host publication2023 3rd International Conference on Energy Engineering and Power Systems, EEPS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages787-791
Number of pages5
ISBN (Electronic)9798350313857
DOIs
StatePublished - 2023
Event3rd International Conference on Energy Engineering and Power Systems, EEPS 2023 - Dali, China
Duration: 28 Jul 2023 → 30 Jul 2023

Publication series

Name2023 3rd International Conference on Energy Engineering and Power Systems, EEPS 2023

Conference

Conference3rd International Conference on Energy Engineering and Power Systems, EEPS 2023
Country/TerritoryChina
CityDali
Period28/07/23 → 30/07/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • consistency verification
  • data inference
  • power grid
  • power system

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