基于负荷细分的差异化用户基线负荷预测
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国家重点研发计划资助项目(2016YFB0901100)


Differential Customer Baseline Load Forecasting Based on Load Subdivision
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    摘要:

    电力用户基线负荷(CBL)预测精度会极大影响需求响应效果的评估。本文基于负荷细分,考虑多维用电行为及其影响因素,通过精细化用户用电行为特征,提出一种考虑用户用电模式差异化的基线负荷预测方法。首先采用Ward-模糊C均值(FCM)聚类法,并结合负荷特性指标,改善用户负荷曲线聚类分析的效果;然后,分析气象、时间等多维影响因素,建立考虑温湿度和气温累积效应等城市微气象因素及节假日社会行为因素的差异化用电行为分析模型,提出温度敏感型、节假日敏感型以及两者均不敏感的精细化用电模式;最后,提出不同用电模式的CBL预测方法,建立综合评估方法分析其预测准确度。算例结果表明,所提算法能进一步提高CBL预测精度。

    Abstract:

    The accuracy of power costumer baseline load (CBL) prediction will greatly affect the evaluation of demand response.In this paper,taking multidimensional electricity behavior and its influencing factors into consideration,a user differentiated baseline load prediction method based on load subdivision is proposed by elaborating user behavior characteristics.This method uses Ward-FCM cluster analysis and combines the load characteristic index to improve the effect of user load curve cluster analysis.Based on the analysis of multi-dimensional influencing factors such as meteorology and time,a refined analysis method of electricity consumption behavior is put forward considering urban micro meteorological factors such as temperature,humidity and temperature cumulative effect and social behavior factors during holidays.The temperature-sensitive,holiday-sensitive and both-insensitive differential power behaviors are obtained.On this basis the customer baseline load forecasting analysis of differentiated power consumption is performed and a comprehensive evaluation model is established to analyze the prediction accuracy.The analysis results show that the proposed algorithm can further improve the accuracy of baseline load forecasting.

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王啸峰,苏慧玲,宋天立,黄奇峰.基于负荷细分的差异化用户基线负荷预测[J].电力工程技术,2018,37(6):33-38

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  • 收稿日期:2018-09-12
  • 最后修改日期:2018-10-18
  • 录用日期:2018-11-12
  • 在线发布日期: 2018-11-28
  • 出版日期: 2018-11-28