IT 최적화 기술을 이용한 지능형전력망 환경의 스마트 빌딩 전력 스케줄링

【With the recent advances in smart grid technologies and the increasing dissemination of smart meters, the power usage of each time unit can be detected in modern smart building environments. Thus, the utility company can adopt different price of electricity at each time slot considering the peak time. Korea government also announces the smart-grid roadmap that includes a law for realtime price of electricity. In this paper, we propose an efficient power scheduling scheme for smart buildings that adopt smart meters and real-time pricing of electricity. Our scheme dynamically changes the power mode of each consumer device according to the change of power rates. Specifically, we analyze the electricity demands and prices at each time, and then perform real-time power scheduling of consumer devices based on collaboration of each device. Experimental results show that the proposed scheme reduces the electricity charge of a smart building by up to 36.4%.】

[1]  Chi Zhou,et al.  Developing ZigBee Deployment Guideline Under WiFi Interference for Smart Grid Applications , 2011, IEEE Transactions on Smart Grid.

[2]  Michael Zeifman,et al.  Disaggregation of home energy display data using probabilistic approach , 2012, IEEE Transactions on Consumer Electronics.

[3]  Massimo Aliberti Green networking in home and building automation systems through power state switching , 2011, IEEE Transactions on Consumer Electronics.

[4]  Taskin Koçak,et al.  Smart Grid Technologies: Communication Technologies and Standards , 2011, IEEE Transactions on Industrial Informatics.

[5]  Jessica Granderson,et al.  Building energy information systems: user case studies , 2011 .

[6]  Seunghyun Park,et al.  Concurrent simulation platform for energy-aware smart metering systems , 2010, IEEE Transactions on Consumer Electronics.

[7]  Ning Lu,et al.  Appliance Commitment for Household Load Scheduling , 2011, IEEE Transactions on Smart Grid.

[8]  Na Li,et al.  Optimal demand response based on utility maximization in power networks , 2011, 2011 IEEE Power and Energy Society General Meeting.

[9]  Vincent W. S. Wong,et al.  Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid , 2010, IEEE Transactions on Smart Grid.

[10]  Hye-Jin Kim,et al.  Power consumption scheduling for peak load reduction in smart grid homes , 2011, SAC '11.

[11]  Hanne Sæle,et al.  Demand Response From Household Customers: Experiences From a Pilot Study in Norway , 2011, IEEE Transactions on Smart Grid.

[12]  H. Vincent Poor,et al.  Scheduling Power Consumption With Price Uncertainty , 2011, IEEE Transactions on Smart Grid.

[13]  Chi-Huang Hung,et al.  Home appliance energy monitoring and controlling based on Power Line Communication , 2009, 2009 Digest of Technical Papers International Conference on Consumer Electronics.

[14]  Dae-Man Han,et al.  Design and implementation of smart home energy management systems based on zigbee , 2010, IEEE Transactions on Consumer Electronics.