In residential energy management (REM), time of use (TOU) of appliances scheduling based on user-defined preferences is an essential task performed by the home energy management controller. This paper devised a robust REM technique capable of monitoring and controlling residential loads within a smart home. The method is based on an improved binary grey wolf accretive satisfaction algorithm (GWASA), which is developed based on four hypotheses that allow time-varying preferences to be quantifiable in terms of time and device-dependent features. Based on household appliances TOU, the absolute satisfaction derived from the preferences of appliance and power ratings, the GWASA can produce optimum energy consumption pattern that will give the customer maximum satisfaction at the predefined user budget. A cost per unit satisfaction index is also established to relate daily consumer expenses with the achieved satisfaction. Simulation results on three peak budgets from $1.5/day to $2.5/day with a step size of $0.5 are carried out to analyze the efficacy of GWASA. Accordingly, the result of each of the scenario is compared with the result obtained from three other different algorithms, namely, BPSO, BGA, BGWO. The simulation results reveal that the proposed demand side residential management based on GWASA offers the least cost per unit satisfaction and maximum percentage satisfaction in each scenario.

在住宅能源管理（REM）中，基于用户定义的偏好进行设备调度的使用时间（TOU）是家庭能源管理控制器执行的一项基本任务。本文设计了一种鲁棒的REM技术，该技术能够监视和控制智能家居中的住宅负载。该方法基于一种改进的二进制灰狼增生满意度算法（GWASA），该算法基于四个假设进行开发，这些假设允许根据时间和与设备相关的特征对时变偏好进行量化。GWASA可以基于家用电器的TOU（从对电器的偏好和额定功率的偏好中得出的绝对满意度）产生最佳的能耗模式，从而以预定义的用户预算为客户提供最大的满意度。还建立了单位成本满意度指数，以将日常消费者支出与所获得的满意度相关联。对三个峰值预算（从$ 1.5 /天到$ 2.5 /天，步长为$ 0.5）进行了仿真结果，以分析GWASA的功效。因此，将每个方案的结果与从其他三种不同算法（即BPSO，BGA，BGWO）获得的结果进行比较。仿真结果表明，在每种情况下，基于GWASA提出的需求侧住宅管理可提供最低的单位满意度成本和最大的百分比满意度。将每个方案的结果与从其他三种不同算法（即BPSO，BGA，BGWO）获得的结果进行比较。仿真结果表明，在每种情况下，基于GWASA提出的需求侧住宅管理可提供最低的单位满意度成本和最大的百分比满意度。将每个方案的结果与从其他三种不同算法（即BPSO，BGA，BGWO）获得的结果进行比较。仿真结果表明，在每种情况下，基于GWASA提出的需求侧住宅管理可提供最低的单位满意度成本和最大的百分比满意度。