Real-time Energy Control Approach for Smart Home Energy Management System

  • Zhou S
  • Wu Z
  • Li J
 et al. 
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This article investigates a real-time energy control approach for a home energy management system, including the electric water heater, air conditioner, clothes dryer, electric vehicle, photovoltaic cell, critical loads, and battery system. A demand response mechanism is proposed to enable households to participate in demand response services. Half-hour-ahead rolling optimization and a real-time control strategy are combined to achieve household economic benefits and ability to deal with complex operating environments. A fuzzy logic controller is utilized to determine battery charging/ discharging power; proper rules are proposed to ensure benefits from operating the battery under the real-time electricity price. The simulation test results indicate that the proposed control approach can optimize the schedule for home appliances and battery charging/ discharging behavior, even if the forecasted information is not accurate. A physical test platform has also been established and tested in the lab to support the operation of the whole system. [ABSTRACT FROM PUBLISHER] Copyright of Electric Power Components & Systems is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Author-supplied keywords

  • ELECTRIC utilities -- Costs
  • ELECTRIC water heaters
  • ENERGY consumption
  • ENERGY management
  • FUZZY logic
  • HOME automation
  • LOAD (Electric power)
  • demand response
  • fuzzy logic controller
  • home energy management system
  • real-time control strategy
  • rolling optimization
  • smart grid

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  • Suyang Zhou

  • Zhi Wu

  • Jianing Li

  • Xiao-ping Zhang

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