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Optimal Home Energy Management for Smart Home using Random Bit Climbing

机译:使用随机位爬升的智能家居优化家庭能源管理

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Home Energy Management Systems (HEMS) has been considered to manage the energy usage at smart homes. In this paper, Optimal Home Energy Management (OHEM) algorithm is introduced to select the time slots, at which the electrical tasks are executed so that the electric power cost and the user comfort are improved. Random Bit Climbing (RBC) optimization method is employed to get an optimal or near-optimal solution that represents the time slots of the home tasks operation. Real-Time Pricing (RTP) is considered for electricity cost. Firstly, the electrical tasks are modeled to determine its main attributes. The objective function of the proposed algorithm is defined as a utility function that minimizes the user conform and the electricity cost. After that, the RBC method is performed to get the optimal or near-optimal solution that minimizes the objective function.Simulation results show that the proposed OHEM algorithm improve the electrical energy cost with reasonable user comfort. Additionally, the degree of improvement for electrical energy cost and user comfort can be adjusted and controlled using a weighting parameter.
机译:人们已经考虑过家庭能源管理系统(HEMS)来管理智能家居中的能源使用。本文介绍了最优家庭能源管理(OHEM)算法来选择执行电气任务的时隙,从而提高了电费成本和用户舒适度。采用随机位爬升(RBC)优化方法来获得表示家庭任务操作的时隙的最佳或接近最佳的解决方案。电费考虑了实时定价(RTP)。首先,对电气任务进行建模以确定其主要属性。所提出算法的目标函数定义为效用函数,该函数可最大程度地减少用户的使用量和电费。仿真结果表明,提出的OHEM算法以合理的用户舒适度提高了电能成本,降低了目标函数的逼近。另外,可以使用加权参数来调节和控制电能成本和用户舒适度的改善程度。

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