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In this study, the optimum run time of each electrical
appliances is scheduled to reduce the total energy consumption
cost in smart homes and to flat the electrical load curve. The
participation of residents in the price-based Demand Response
(DR) program through the time-varying price tariffs, largely
determines their energy consumption habits. The energy
management for the smart home, which includes distributed
generation, energy storage system, electric vehicle (EV) and
controllable electrical appliances is optimized by using genetic
algorithm method. Thanks to bidirectional power flow
technology, the excess energy of EVs, considered as a mobile
energy storage system and the distributed generation unit, can be
transferred to the smart home or to the grid. EVs are an
important option to supply energy demands at smart home
during peak hours and to eliminate instabilities such as voltage
drop and frequency fluctuation that may occur in the grid
1.st International Conference Energy Systems Engineering
ıcese'17
Efe Isa Tezde
H. Ibrahim Okumus