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基于大数据分析的智能电网中台区线损预测系统设计

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在分析智能电网中台区线损预测内涵的基础上,设计了一套基于大数据分析的智能电网中台区线损预测系统.该系统采用Hadoop和Spark搭建高性能计算平台,通过数据挖掘和机器学习技术,实现台区线损的精准预估和趋势预测.系统测试表明,LSTM模型在多时间尺度线损预测任务中表现最优,月、日、时尺度的MAPE分别控制在1.25%、2.93%、6.18%以内,可有效指导配电网的精益化管理.
Design of Prediction System for Smart Grid Power Substation Line Loss Based on Big Data Analysis
Based on the analysis of the connotation of line loss prediction in smart grid substations,a smart grid substation line loss prediction system based on big data analysis was designed. The system uses Hadoop and Spark to build a high-performance computing platform,and through data mining and machine learning techniques,achieves accurate estimation and trend prediction of line losses in the substation area. System testing shows that the LSTM model performs the best in multi time scale line loss prediction tasks,with monthly,daily,and hourly MAPE controlled within 1.25%,2.93%,and 6.18%,respectively,effectively guiding lean management of distribution networks.

smart gridsubstation line lossbig data analysis

郭亚光

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国网临汾市尧都区供电公司,山西临汾 041000

智能电网 台区线损 大数据分析

2024

自动化应用
重庆西南信息有限公司

自动化应用

影响因子:0.156
ISSN:1674-778X
年,卷(期):2024.65(24)