南京市電力負荷特征及夏季極端負荷與氣象條件關系
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中國長江電力股份有限公司科研課題(241802002)“受電區(qū)域氣象條件對用電負荷的影響研究“資助


Characteristics of Electric Loads in Nanjing and Relationship between Extreme Loads and Meteorological Conditions in Summer
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    摘要:

    基于南京地區(qū)2014—2016年逐日電力負荷資料,采用諧波分析、功率譜等方法分析該地區(qū)電力負荷的變化規(guī)律及其與自然周的關系,并對極端電力負荷日中離差曲線型與氣溫、濕度等氣象要素及環(huán)流形勢的關系進行分析。結果表明:南京地區(qū)電力負荷的季節(jié)變化呈雙峰型;在季節(jié)內(nèi)(月際)尺度上,存在30 d周期;在月內(nèi)尺度上,存在7 d周期且與自然周同步。夏季極端負荷日離差曲線主要存在3種類型:典型雙峰型(Ⅰ)、單峰型(Ⅱ)、非典型雙峰型(Ⅲ)。Ⅰ型和Ⅲ型與氣溫和炎熱指數(shù)均呈顯著正相關,而3種類型都與相對濕度呈顯著負相關。Ⅰ型對應環(huán)流場上副高持續(xù)控制南京地區(qū),冷空氣活動偏弱,氣溫日變化小;Ⅱ型對應冷空氣活動頻繁,副高具有東西擺動特征,南京常出現(xiàn)陣雨或雷陣雨天氣;Ⅲ型對應的副高強度弱于Ⅰ型,冷空氣強度弱于Ⅱ型。采用逐步回歸方法建立極端負荷日的預測模型,3種型的平均相對誤差分別為6.4%、5.6%和5.3%,較好地對極端電力負荷進行了定量預報。

    Abstract:

    Based on the daily power load data in Nanjing from 2014 to 2016, using the harmonic analysis and power spectrum method, etc., the study analyzes the change rule and characteristics of power loads in Nanjing, and the relationship between the daily curve of power load and the meteorological elements such as temperature and humidity in extreme power load days. The results show that the seasonal variation of power loads in Nanjing is mainly bimodal. On the intramonth scale, there is a significant 7days period change, which is significantly corresponding to weekly circulation. There are three types of daily extreme load deviation curves: typical bimodal (Ⅰ), unimodal (Ⅱ), and atypical bimodal (Ⅲ). The typesⅠand Ⅲ show significant positive correlation with temperature and hotness index, while all the three types show significant negative correlation with relative humidity. Then, the type Ⅰcorresponds to the circulation controlled by a strong and stable subhigh over Nanjing, weak cold air activity, and small temperature diurnal variation. The typeⅡ happens while Nanjing is affected by frequent cold air activities and the eastwest swing subtropical high, when showers or thunderstorms usually happen in Nanjing. The intensity of the subtropical high corresponding to type Ⅲ is weaker than that to typeⅠ, and the degree of cold air activity is weaker than that to typeⅡ. The stepwise regression method is adopted to establish prediction models for different types of extreme load days. The average relative errors of the prediction models based on the three types are 6.4%, 5.6%, and 5.3%, respectively, which can provide good quantitative power load forecasts for extreme power load days in Nanjing.

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李艷,俞劍蔚,蔡薌寧,范曉青,黃琰.南京市電力負荷特征及夏季極端負荷與氣象條件關系[J].氣象科技,2021,49(4):637~646

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  • 收稿日期:2020-07-02
  • 定稿日期:2021-03-05
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  • 在線發(fā)布日期: 2021-08-23
  • 出版日期: 2021-08-31
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