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基于风电机组启停频度的风电间歇性定量刻画及分析

Translated title of the contribution: Quantitative measurement and analysis of wind power intermittence based on start-stop frequency of wind turbines
  • HKU
  • School of Energy Science and Engineering, Harbin Institute of Technology
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

The quantitative analysis of wind power intermittency is the basic work for wind power integration with high efficiency and safety. Firstly, the frequency of start-stop of wind turbine in unit time is defined as a new parameter to describe the intermittence of wind power. Based on the metric, the data from two typical wind farms that located in the northern area of China is used to analyze the seasonal and nycterohemeral variation characteristics of wind power intermittency. The probability distribution of the frequency of start-stop of wind turbine is assessed in this research as well. The results show that intermittent characteristics has a large seasonal variation difference but similar nycterohemeral variations charactiscs. Moreover, wind power intermittency is generally stronger in daytime. The longitudinal time series analysis method is used to assess the probability distribution of the start-stop frequency of wind turbines at different time. The Exponential2 function is used to fit this distribution. Next, function adaptability of data from different years are further studied. Finally, the application feasibility of this parameter in real scene is discussed.

Translated title of the contributionQuantitative measurement and analysis of wind power intermittence based on start-stop frequency of wind turbines
Original languageChinese (Traditional)
Pages (from-to)342-350
Number of pages9
JournalTaiyangneng Xuebao/Acta Energiae Solaris Sinica
Volume42
Issue number4
DOIs
StatePublished - 28 Apr 2021

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

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