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Based on the above assumptions, the optimal consumption schedule of smart household appliances and EVs for each aggregator is developed.
The system can also be used to monitor electricity consumption, schedule and time appliances, and set up device alerts and notifications.
The energy consumption schedule and nodal prices at bus 10155 in a given day are depicted in Figs. 7 and 8, respectively.
The use of adaptive diffusion makes it possible for consumers to find the optimum energy consumption schedule with a small number of information exchanges.
Open image in new window Fig. 4 Energy consumption schedule of bus 10155 in Scenario I Open image in new window Fig. 5 Nodal price of bus 10155 in Scenario I.
Open image in new window Fig. 7 Energy consumption schedule of bus 10155 in Scenario II Open image in new window Fig. 8 Nodal prices of bus 10155 in Scenario II.
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Household energy consumption scheduling becomes complicated since the existence of a PV-battery system.
The punishment is implemented by the participating consumers using a different energy consumption scheduling.
Assume that each user owns a smart meter with the function of energy consumption scheduling.
Demand side energy consumption scheduling is a well-known issue in the smart grid research area.
At the beginning of each billing cycle, the consumers determine the consumption scheduling actions for the next L days.
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