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考虑集群辨识的海量用户负荷分层概率预测
作者:
作者单位:

上海交通大学电子信息与电气工程学院,上海市 200240

摘要:

随着电力公司等传统能源企业向综合能源服务商的加速转型,原有的粗放式用户用电管理模式逐渐难以满足电力营销管理的需求。针对海量用户场景提出了用电模式分层聚类方法及用户集群辨识模型。基于用户集群辨识结果提出了条件残差模拟负荷概率预测模型,进行负荷分层概率预测,以实现对用户精细化用电管理。通过典型案例验证了所提方法的可行性与优越性。

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基金项目:

国家重点研发计划资助项目(2016YFB0900100);上海科委科研计划资助项目(18DZ1100303)。

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作者简介:


Load Stratified Probability Forecasting of Massive Users Considering Cluster Identification
Author:
Affiliation:

School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Abstract:

With the accelerated transformation of traditional energy companies such as power companies to integrated energy service providers, the original extensive power management model of users has gradually become difficult to meet the needs of power marketing management. A hierarchical clustering method of electricity consumption patterns and a model of users cluster identification are proposed for massive user scenarios. Based on the identification results of user clusters, this paper proposes a prediction model of conditional residual simulation load probability. The prediction of load hierarchical probability is carried out to realize the refined power management of users. A typical case verifies the feasibility and superiority of the proposed method.

Keywords:

Foundation:
This work is supported by National Key Research Program of China (No. 2016YFB0900100) and Scientific Research Project of Shanghai Science and Technology Committee (No. 18DZ1100303)Foundation:.
引用本文
[1]顾洁,孟璐,郑睿程,等.考虑集群辨识的海量用户负荷分层概率预测[J/OL].电力系统自动化,http://doi. org/10.7500/AEPS20200423008.
GU Jie, MENG Lu, ZHENG Ruicheng, et al. Load Stratified Probability Forecasting of Massive Users Considering Cluster Identification[J/OL]. Automation of Electric Power Systems, http://doi. org/10.7500/AEPS20200423008.
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  • 收稿日期:2020-04-23
  • 最后修改日期:2020-10-30
  • 录用日期:2020-09-21
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