TY - GEN
T1 - Residential load management system for future smart energy environment in GCC countries
AU - Refaat, Shady S.
AU - Abu-Rub, Haitham
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/8/17
Y1 - 2015/8/17
N2 - Electricity consumption has increased substantially over the last decade. According to the Gulf Research Center (2013), residential sector represents the largest portion of electricity consumption (about 50%) in the Gulf Cooperation Council (GCC) region, due to substantial growth of electrical residential appliances. Therefore, we present a novel online smart residential load management system that is used to online monitor and control power consumption of the loads toward optimizing energy consumption, balancing electric power supply, reducing peak demand, and minimizing energy bill, while considering residential customer preferences and comfort level. The presented online algorithm manages power consumption by assigning the residential load according to utilities power supply events. The input data to the management algorithm is set based on the categorized loads according to: importance (vital, essential, and non-essential electrical loads), electrical power consumption, electricity bill limitation, utilities power limitation, and load priority. The data are processed and fed to the presented algorithm, which accurately manages the power of dwelling loads using external controlled disconnectors. The proposed online algorithm yields to improve the overall grid efficiency and reliability, especially during the demand response periods. Simulation results demonstrate the validity of the proposed algorithm.
AB - Electricity consumption has increased substantially over the last decade. According to the Gulf Research Center (2013), residential sector represents the largest portion of electricity consumption (about 50%) in the Gulf Cooperation Council (GCC) region, due to substantial growth of electrical residential appliances. Therefore, we present a novel online smart residential load management system that is used to online monitor and control power consumption of the loads toward optimizing energy consumption, balancing electric power supply, reducing peak demand, and minimizing energy bill, while considering residential customer preferences and comfort level. The presented online algorithm manages power consumption by assigning the residential load according to utilities power supply events. The input data to the management algorithm is set based on the categorized loads according to: importance (vital, essential, and non-essential electrical loads), electrical power consumption, electricity bill limitation, utilities power limitation, and load priority. The data are processed and fed to the presented algorithm, which accurately manages the power of dwelling loads using external controlled disconnectors. The proposed online algorithm yields to improve the overall grid efficiency and reliability, especially during the demand response periods. Simulation results demonstrate the validity of the proposed algorithm.
KW - Demand response
KW - Demand side management
KW - Load management
KW - Residential load
KW - Smart Grid
UR - http://www.scopus.com/inward/record.url?scp=84953257508&partnerID=8YFLogxK
U2 - 10.1109/SGRE.2015.7208735
DO - 10.1109/SGRE.2015.7208735
M3 - Conference contribution
AN - SCOPUS:84953257508
T3 - 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015
BT - 2015 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st Workshop on Smart Grid and Renewable Energy, SGRE 2015
Y2 - 22 March 2015 through 23 March 2015
ER -