The demand-side management in the smart grid can be considered as a multi objective optimization problem. An efficient energy consumption schedule should minimize the peak-to-average ratio of the total energy demand, the total energy costs, as well as each user’s individual daily electricity charges. In this paper, using the NSGA-II as a genetic based algorithm is proposed to solve this optimization problem to obtain an optimum user’s energy consumption schedule. The simulation results show that using the optimum consumption schedule not only the peak-to-average ratio of the total energy demand is reduced, but also the charge of each user can reduce effectively.
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