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Scheduling techniques and coordination among appliances are explained in Section 4.Section 5 describes the FRs along with results and discussion of both cases: coordination and without coordination.At the end, Section 6 states the conclusion and future work. In the literature, many existing techniques are studied for the scheduling of household load through various optimization techniques.  propose a system model for scheduling the home appliances and for integrating the Renewable Energy Sources (RESs).For this purpose, authors implement dynamic programming to schedule the household appliances and use GT to sell surplus energy to neighbors and utility.A novel Home Energy Management System (HEMS) is proposed by Sheraz et al. Genetic Algorithm (GA), CSA and crow search algorithms are implemented by authors for the load management of a smart building having thirty homes.
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However, price during a specific time period can be changed because of stress events happened in the power system.RTP pricing scheme is communicated to consumers before the start of a time period and is updated after each time period.The rate of this pricing scheme depends upon the energy consumption, energy generation and response of consumers in the previous time period. The target of the EMS is to reduce the electricity cost.Coordination among appliances is integrated to increase the flexibility of the system using GT and a comparison is conducted among its three variants, that is, Shapley Value (SV), Nash Equilibrium (NE) and Zero Sum (ZS).