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Fuzzy energy management controller and scheduler for smart homes

机译:智能家居的模糊能源管理控制器和调度器

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The integration of information and communication technologies in traditional grid brings about a smart grid. Energy management plays a vital role in maintaining the sustainability and reliability of a smart grid which in turn helps to prevent blackouts. Energy management at consumer's side is a complex task, it requires efficient scheduling of appliances with minimum delay to reduce peak-to-average ratio (PAR) and energy consumption cost. In this paper, the classification of appliances is introduced based on their energy consumption pattern. An energy management controller is developed for demand side management. We have used fuzzy logic and heuristic optimization techniques for cost, energy consumption and PAR reduction. Fuzzy logic is used to control the throttleable and interruptible appliances. On the other hand, the heuristic optimization algorithms, BAT inspired and flower pollination, are employed for scheduling of shiftable appliances. We have also proposed a hybrid optimization algorithm for the scheduling of home appliances, named as hybrid BAT pollination optimization algorithm. Simulation results show a significant reduction in energy consumption, cost and PAR. (C) 2018 Elsevier Inc. All rights reserved.
机译:信息和通信技术在传统电网中的集成带来了智能电网。能源管理在维持智能电网的可持续性和可靠性方面起着至关重要的作用,从而有助于防止停电。消费者方的能源管理是一项复杂的任务,它要求对设备进行高效的调度,并以最小的延迟来降低峰均比(PAR)和能耗成本。本文根据电器的能耗模式介绍电器的分类。开发了一种能源管理控制器,用于需求侧管理。我们已经使用模糊逻辑和启发式优化技术来降低成本,降低能耗和降低PAR。模糊逻辑用于控制可节流和可中断的设备。另一方面,启发式优化算法(BAT启发式和花朵授粉)用于调度可移动设备。我们还提出了一种用于家用电器调度的混合优化算法,称为混合BAT授粉优化算法。仿真结果表明,显着降低了能耗,成本和PAR。 (C)2018 Elsevier Inc.保留所有权利。

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