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基于云计算的家庭智能用电策略 被引量:26

A Residential Smart Power Utilization Strategy Based on Cloud Computing
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摘要 对智能小区的居民用电行为展开研究,基于云计算平台和并行关联规则Apriori算法,挖掘出了用户用电行为间的关联规则,根据挖掘出的关联规则使用遗传算法对家庭用电时间分布进行合理规划,达到经济用电的目标,给出了行之有效的智能用电策略。由供电局将用户的智能用电策略以短信等交互方式传递给智能用电家庭。经实例验证,文中基于云计算平台和并行Apriori算法的居民用电行为分析结果是有效的,可使居民高效智能用电,节约家庭能耗。 The residential electricity consumption behaviors in smart residential areas are researched.Based on the cloud computing platform and parallel Apriori algorithm,association rules among residential electricity consumption behaviors are mined out.According to the mined association rules,the household electricity time consumption distribution is reasonably planned by the genetic algorithm to achieve the goal of economical power.An effective smart power utilization strategy is given.The power supply bureau can notify residents of the smart power strategies through short message service(SMS)or in other interactive ways.Experimental results show that the residential electricity consumption behavior based on cloud computing platform and parallel Apriori algorithm are effective in guiding residents to save home energy in efficient and intelligent use of power.
作者 郭晓利 于阳
出处 《电力系统自动化》 EI CSCD 北大核心 2015年第17期114-119 133,共7页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(51277023)~~
关键词 云计算 并行Apriori算法 用电行为 智能用电 cloud computing parallel Apriori algorithm electricity consumption behavior smart power utilization
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参考文献4

  • 1SILVA D,VIEIRA S,LIMA C,et al.Home energy saving adviser system. International Conference on Power Engineering,Energy and Electrical Drives . 2011
  • 2IGAKI H,SETO H,FUKUDA M,et al.Mashing up multiple logs in home network system for promoting energy-saving behavior. 8th Asia-Pacific Symposium on Publication Information and Telecommunication Technologies (APSITT) . 2010
  • 3University of California,Irvine.UCI machine learning repository. http://archive.ics.uci.edu/ml/index.html . 2012
  • 4Makonin, S.,Bartram, L.,Popowich, F.A Smarter Smart Home: Case Studies of Ambient Intelligence. Pervasive Computing, IEEE . 2013

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