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Power System Frequency Prediction Method Considering New Energy Access Ratio and Frequency Support Capacity

  • Yixing Zhang
  • , Boyang Chen
  • , Xi Yang
  • , Ding Li
  • , Fengrui Yang
  • , Boyu Qin
  • Xi'an Jiaotong University
  • State Grid Gansu Electric Power Company Material Company

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

With the growing demand for electricity around the world, the energy crisis and environmental issues are becoming increasingly severe. Therefore, it is imperative to develop a new type of power system primarily based on new energy generation. However, as the rate at which renewable energy is being utilized increases, synchronous units are gradually replaced, the rotational moment of inertia of the power system decreases, the frequency regulation ability diminishes, and the frequency stability issue under perturbation events becomes more and more prominent. At the same time, the current frequency dynamic analysis method is difficult to meet the frequency stability analysis under the high proportion of new energy scenarios. Therefore, this paper considers the ability of new energy to actively carry out frequency support, based on the regression decision tree model, establishes a power system frequency prediction model based on the new energy penetration rate, the proportion of new energy units actively involved in frequency control, the new energy unit control parameters, and other key factors, and accurately predicts the maximum frequency deviation and the steady-state frequency deviation of the power system after power perturbation, while the importance of each control parameter is analyzed. And simulations are carried out in the test system to ascertain the efficacy of the introduced method.

Original languageEnglish
Title of host publication2024 9th International Conference on Power and Renewable Energy, ICPRE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1759-1764
Number of pages6
ISBN (Electronic)9798350377460
DOIs
StatePublished - 2024
Event9th International Conference on Power and Renewable Energy, ICPRE 2024 - Guangzhou, China
Duration: 20 Sep 202423 Sep 2024

Publication series

Name2024 9th International Conference on Power and Renewable Energy, ICPRE 2024

Conference

Conference9th International Conference on Power and Renewable Energy, ICPRE 2024
Country/TerritoryChina
CityGuangzhou
Period20/09/2423/09/24

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

  • Frequency prediction
  • Frequency support
  • New energy access scale
  • Regression decision tree

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