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西安市居民用电量对气象因子的响应及预测

卢珊高红燕李建科张宏芳浩宇张曦   

  1. 陕西省气象服务中心,陕西西安710015
  • 出版日期:2017-10-31 发布日期:2017-10-31
  • 作者简介:卢珊(1985—),女,硕士,工程师,主要从事应用气象及专业气象研究. E-mail:lushan660@163.com。
  • 基金资助:

    陕西省自然科学基金(2016JM4020)、中国气象局预报员专项(CMAYBY2014-070)共同资助


Response of Citizens Power Consumption to Meteorological Factors and Its Forecast in Xi’an City

LU Shan, GAO Hongyan, LI Jianke, ZHANG Hongfang, HAO Yu, ZHANG Xi   

  1. Shaanxi Meteorological Service Center, Xi’an 710015, China
  • Online:2017-10-31 Published:2017-10-31

摘要:

利用2010年2月1日至2013年8月31日西安市逐小时电力负荷资料及对应时段地面气象观测站数据,分析西安电力负荷的变化特征,研究气象敏感负荷与主要气象因子的关系。结果表明:电力负荷在不同时间尺度上呈现出不同变化特征,夏季和冬季是一年中电力负荷的高峰期;极端电力负荷出现在夏冬两季,其中夏季极端电力负荷出现频率占总数的74%;相比于其他气象因子,气温与气象敏感负荷的相关性最强,在5—9月呈正相关,10月至次年4月呈负相关,逐日气象负荷率随日平均气温的增加先逐渐减小,再逐渐增加,当日平均气温为17 ℃时,气象负荷率最小;日最高气温34 ℃为夏季引起西安市最大电力负荷增加的初始气温敏感值,36 ℃为强气温敏感值,38 ℃为极强气温敏感值,日最低气温-2 ℃为冬季引起西安市最大电力负荷增加的初始气温敏感值,-4 ℃为强气温敏感值,-7 ℃为极强气温敏感值。

关键词: 气象敏感负荷, 气象因子, 回归分析

Abstract:

Based on the hourly power load data and meteorological data in Xi’an from Feb 1 2010 to Aug 31 2013, the variation of power load and relationship between meteorological sensitive load and meteorological factors were analyzed. The results show that power load presented different characteristics at different time scales, summer and winter were the two peak periods of power load in a year. Extreme power load occurred in summer and winter, and in summer it accounted for 74% of the total. Compared with other meteorological factors, the correlation between temperature and meteorological sensitive load was strongest, which was positive from May to September and negative from October to next April. With the increase of daily mean temperature, the daily meteorological sensitive load rate decreased first, and then increased gradually. When the daily average temperature was 17 ℃, the meteorological sensitive load rate was lowest. When daily maximum temperature reached 34 ℃, it was the initial sensitive value of maximum power load in Xi’an in summer, and 36 ℃was the strong sensitive temperature value, 38 ℃ was the extreme sensitive temperature value. When daily minimum temperature reached -2 ℃, it was the initial sensitive value of the maximum power load in Xi’an in winter, -4 ℃ was the strong sensitive temperature value, and -7 ℃ was the extreme sensitive temperature value.

Key words:
meteorological sensitive load,
meteorological factor, regression analysis

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