Social Networking Reduces Peak Power Consumption in Smart Grid


Minimizing the height power consumption of electrical appliances below delay requirements is shown to be NP-arduous. To handle this, we propose a “family arrange” approach that partitions users into groups and schedules users' appliances to minimize the peak power consumption of each group. Our theme leverages the social network topology and statistical energy usage patterns of users. To partition users into groups with the potential of reducing peak power consumption, our distributed clustering scheme seeks such a partition of users into groups that the entire power consumption in every cluster of users achieves minimum variance. Then, given a collection of jobs of users' appliances to be scheduled in the following scheduling period, we have a tendency to use a distributed scheduling algorithm to minimize the height power consumption of each cluster of users. Our simulation results demonstrate that our theme achieves a vital reduction in user payments, peak power consumption, and fuel cost.

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