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In this paper, a demand side management (DSM) scheme is used to make energy utilization more efficient. The DSM scheme encourages the consumer to change energy utilization patterns which benefit the utility. In return, the consumer gets some incentives from the utility. The objectives of the proposed DSM system include: electricity bill reduction, reduced peak to average ratio (PAR), and maximization of consumer comfort. In the proposed system, the electrical devices are scheduled by using elephant herding optimization (EHO) and adaptive cuckoo search (ACS) algorithms. Moreover, a new algorithm called hybrid elephant adaptive cuckoo (HEAC) is proposed which uses the features of both former algorithms. A comparison of these algorithms is also presented in terms of three performance parameters. The HEAC shows better performance as compared to EHO and ACS which is evident from the simulation results. Different electricity tariffs are introduced by the utility to provide incentives to the consumers. A regional based time of use (ToU) tariff is used to make the system effective for different types of regions. Moreover, this enables the consumers to act according to the regional environment. The coordination can play a very important role in cost reduction as well as in consumer comfort maximization. The coordination is incorporated among the electrical devices by using cooperative game theory (GT) and dynamic programming (DP). Extensive simulations are performed to show the effectiveness of the proposed scheme in terms of electricity utilization cost, PAR reduction, and consumer comfort maximization.

Exploiting Game Theoretic Based Coordination Among Appliances in Smart Homes for Efficient Energy Utilization