Hardware Design of Smart Home Energy Management System With Dynamic Price Response

Qinran Hu, Fangxing Li
2013 IEEE Transactions on Smart Grid  
The smart grid initiative and electricity market operation drive the development known as demand-side management or controllable load. Home energy management has received increasing interest due to the significant amount of loads in the residential sector. This paper presents a hardware design of smart home energy management system (SHEMS) with the applications of communication, sensing technology, and machine learning algorithm. With the proposed design, consumers can easily achieve a
more » ... , price-responsive control strategy for residential home loads such as electrical water heater (EWH), heating, ventilation, and air conditioning (HVAC), electrical vehicle (EV), dishwasher, washing machine, and dryer. Also, consumers may interact with suppliers or load serving entities (LSEs) to facilitate the load management at the supplier side. Further, SHEMS is designed with sensors to detect human activities and then a machine learning algorithm is applied to intelligently help consumers reduce total payment on electricity without or with little consumer involvement. Finally, simulation and experiment results are presented based on an actual SHEMS prototype to verify the hardware system. Index Terms-Controllable load, demand response, dynamic pricing, embedded system, machine learning, optimal control strategies, peak shaving, remote operation, smart home energy management system (SHEMS). NOMENCLATURE Signals from sensors. User's activity. Temperature in electrical water heater at time , . Ambient temperature at time , . Thermal resistance of tank walls, . Rate of energy extraction when water is in demand at time . Status of the hot water demand at time , ON/OFF.
doi:10.1109/tsg.2013.2258181 fatcat:xdp6usggkfc6vly4gtcwiszlva