Scheduling Method for Electric Heater in HEMS Considering User’s Comfort
Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109151Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF
 Qinran Hu and Fangxing Li, “Hardware Design of Smart Home Energy Management System with Dynamic Price Response”, IEEE Trans. Smart Grid, Vol. 4, NO. 4, December 2013.
 Pengwei Du and Ning Lu, “Appliance Commitment for Household Load Scheduling”, IEEE Trans. Smart Grid, Vol. 2, NO. 2, June 2011.
 Kornschnok Dittawit and Finn Arve Aagesen, “Home Energy Management System for Electricity Cost Savings and Comfort Preservation”, Norwegian University of Science and Technology.
 Suyang Zhou, Zhi Wu, Jianing Li and Xiao-ping Zhang, “Real-time Energy Control Approach for Smart Home Energy Management System”, School of Electrical, Electronic and Computer Engineering, University of Birmingham, Birmingham, UK. 05 Feb 2014.
 Je-Seok Shin, Yong-Sung Kim, Hee-Jeong Park, Young-Bae Park and Jin-O Kim, “Study on Modeling Usage Pattern of Appliances in HEMS Using Copula Function”, KIEE July 2015.
 M.Tavakoli, Danial Ahmadi, “Stochastic Modeling for the Next Day Domestic Demand Response Applications”, IEEE Trans. on Power Systems“, Issue.99, pp.1-14, 2015.01.
 Chengshan Wang, “A novel Traversal-and-pruning algorithm for household load scheduling”, Applied Energy, 1430-1438, 2013.
 Hyun-Seung Lee, Je-Seok Shin, Do-Eun Oh, Jung-Il Lee and Jin-O Kim, “Optimal Scheduling of Electric Water Heater Considering User Comfort For HEMS”, KIEE July 2015.
 “2008 ASHRAE Handbook-HVAC Systems and Equipment” Amer. Soc. Heating, Refrigerating and Air-Conditioning Eng., Inc., 2008 (Online). Available:http://www.Knovel.com/web/portal/browse/display?_EXT_K NOVEL_DISPLAY_bookid=2396.