• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

电力建设 ›› 2015, Vol. 36 ›› Issue (10): 99-104.doi: 10.3969/j.issn.1000-7229.2015.10.015

• 电力规划新技术 • 上一篇    下一篇

考虑相关因素统一修正的节假日负荷预测模型

苗键强,童星,康重庆   

  1. 电力系统及发电设备控制和仿真国家重点实验室(清华大学电机系),北京市 100084
  • 出版日期:2015-10-01
  • 作者简介:苗键强(1992),男,硕士研究生,研究方向为能源互联网、负荷预测; 童星(1989),男,博士研究生,IEEE学 生 会 员 , 研究方向为负荷预测; 康重庆(1969),男,教授,研究方向为低碳电力、负荷预测、电力规划等。
  • 基金资助:

    国家电网公司科技项目(SGHB0000KXJS1400044,新形势下电力需求及售电市场分析预测技术研究)。

Holiday Load Forecasting Model Considering Related Factor with Unified Correction

MIAO Jianqiang, TONG Xing, KANG Chongqing   

  1. State Key Lab of Control and Simulation of Power Systems and Generation Equipments (Department of Electrical Engineering, Tsinghua University), Beijing 100084, China
  • Online:2015-10-01

摘要:

能源互联网正在逐步影响电网的规划建设方式,其对于相关的负荷预测技术也提出了更高的要求。节假日负荷预测由于存在与正常工作日差异较大且历史数据较少的原因,其负荷预测的效果往往不理想。通过相关因素统一修正模型对气象、时间等相关因素进行修正处理之后,得到统一相关因素影响下的正常工作日数据。考虑“近大远小”的原则,对于正常工作日和节假日负荷曲线之间的相关性进行分析,并基于点对点倍比预测模型提出节假日负荷预测模型,该模型能够自动削弱历史中不正常数据对于预测精度的影响。将提出的预测方法应用于我国北方某城市和某地区的节假日负荷预测,算例分析结果显示预测精度能够满足实际需要,可以为相关电力部门节假日负荷预测提供一定的参考价值。

关键词: 负荷预测, 节假日, 相关因素, 点对点倍比

Abstract:

The energy internet is gradually impacting the planning and construction way of power grid, which puts harder request on the prediction technology of related factors. Due to the huge differences between holidays and weekdays and the lack of historic data, the results of load prediction for holidays are not so good. Weather, date and other related factors were corrected by the unified correction model of related factor, and then the data for normal weekdays impacted by unified related factors was obtained. Considering the principle of ‘emphasizing the near and belittling the long’, the relevance of load curves between normal weekdays and holidays was analyzed, and the load forecasting model was proposed based on the point-to-point analogy, which could reduce the prediction error caused by the abnormal historic data automatically. The proposed prediction method was applied to the holiday load forecasting in one of the northern cities and districts in China. The example analysis results show that the prediction accuracy can satisfy the actual requirements, which can provide a certain reference value for the holiday load forecasting of related power sector.

Key words: load forecasting, holiday, related factor, point-to-point analogy

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