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In this paper, a real-time optimal appliance usage strategy is proposed based on binary particle swarm algorithm, participated by both energy suppliers and end users. Under the multi end-users and time-of-use electricity prices circumstances, the total electricity bills can be generated with different appliance usage pattern: random, single optimal objective and double optimal objectives, resulting...
In this paper, an optimal real-time home energy management to regulate the residential appliances is proposed considering renewable energy resources included in the grid. The appliances can be classified into different groups, where the time shiftable appliances are participated in the scheme to schedule their operational period via the price incentive. An improved binary swarm optimization algorithm...
In this paper, an optimal strategy for appliance management is proposed participated by both energy suppliers and end users. Through mathematical description of the appliance operation, a suitable work plan timtable for the electric appliances is derived to satisfy both the power limits requested from the power suppliers and the least cost expectation from user side. Furthermore, the utility suppliers...
In this paper, a real-time optimal appliance usage strategy is proposed based on binary particle swarm algorithm, participated by both energy suppliers and customers, together with renewable resources. With different time-of-use electricity prices, a time table for the appliance operation is derived with the least tariff objective considering the personal habits and characteristics of the appliances...
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