Load scheduling and energy allocation optimization algorithm for intelligent home appliances
To address the problem of high energy consumption in household electricity usage and to improve the user revenue from electricity supply and use,an energy scheduling approach was proposed for loads with electrical differences in households.Firstly,the household electrical loads were divided into elastic loads and non-elastic loads based on the transferable attributes.Then,an optimization model for load scheduling of intellectualized electrical apparatus was proposed by jointly considering distributed renewable energy resources and energy storage devices.Based on the Lyapunov optimization theory,an algorithm for time-varying electricity pricing was designed to allocate energy for multiple home appliances.The algorithm fully considered the load response and the scheduling optimization of different intelligent appliances.Theoretical performance analysis demonstrates that the proposed algorithm achieves asymptotic optimality without requiring any priori statistical information of the system.Finally,simulations were conducted to validated the user revenue improvement capability of the proposed algorithm.Compared to the allocation algorithm that did not take into account the actual needs of various home appliances and tolerable delay,the proposed algorithm can increase the user revenue by 11.2%.
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