| 引用本文: | 徐青山,王文帝,林章岁,李喜兰,丁茂生.面向行业大数据特征挖掘的电力经理指数指标体系的建立与应用[J].电力自动化设备,2015,35(7): |
| XU Qingshan,WANG Wendi,LIN Zhangsui,LI Xilan,DING Maosheng.Establishment and application of EMI indicator system orienting to massive industrial data mining[J].Electric Power Automation Equipment,2015,35(7): |
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| 摘要: |
| 从大量的电力数据和行业数据中选取所需指标数据，形成行业电力经理指数EMI（Electricity Managers Index）指标体系。利用统计检验-粗糙集分析法筛选出关键指标，优化行业电力经理指数指标体系，并提出基于行业电量经理指数指标体系进行行业用电趋势预测的方法。运用所提方法对福建省典型行业的用电趋势进行分析和预测，结果证实了方法的可行性和有效性。 |
| 关键词: 用电预测 指标体系 先行指标 格兰杰检验 粗糙集 电力经理指数 |
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| 基金项目:国家科技支撑计划项目（2013BAA01B00） |
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| Establishment and application of EMI indicator system orienting to massive industrial data mining |
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XU Qingshan1, WANG Wendi1, LIN Zhangsui2, LI Xilan2, DING Maosheng3
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1.School of Electrical Engineering，Southeast University，Nanjing 210096，China;2.Fujian Electric Power Company Economic Research Institute，Fuzhou 350012，China;3.State Grid Ningxia Electric Power Company，Yinchuan 750001，China
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| Abstract: |
| The required indicator data are selected from massive electrical power data and industrial data to form an EMI（Electricity Managers Index） indicator system. The statistical test-rough set theory is applied to select the key indicators and optimize the EMI indicator system. It is proposed to predict the industrial power usage trend based on the optimized EMI indicator system. The power usage trends of the typical industries in Fujian province are predicted by the proposed method and the results show its feasibility and effectiveness. |
| Key words: electricity forecasting indicator system leading indicators Granger causality test rough set EMI |
