Demand side management for residential areas using hybrid bacterial foraging and bat optimization algorithm: Demand side management using hybrid bacterial foraging and bat optimization algorithm

Mian Muhammad Naeem Abid, N. Javaid, M. H. Rahim, S. Aslam
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引用次数: 4

Abstract

In this work, two meta-heuristic bio-inspired algorithms and our proposed hybrid technique (Bacterial foraging optimization algorithm (BFA) and BAT algorithm (BA) (HBB)) are proposed for optimizing and scheduling the appliances of residential consumers. BFA, BA and our proposed technique HBB are used for scheduling the appliances in order to find the optimal solution. Appliances have different power ratings and power consumption patterns. Three different operational time intervals of 5, 30 and 60 minutes are taken in this work and their comparison is carried out. Eighteen appliances are considered and they are classified into three categories: interruptible, non-interruptible and base load appliances. Single home scenario is considered in this work. Results show that proposed technique has significantly reduced electricity cost and peak-to-average ratio. Consumers have not only supposed to pay less electricity bill, however, utilities also have to bear less stress especially in on-peak hours.
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基于细菌混合觅食和蝙蝠优化算法的小区需求侧管理:基于细菌混合觅食和蝙蝠优化算法的需求侧管理
在这项工作中,提出了两种元启发式生物启发算法和我们提出的混合技术(细菌觅食优化算法(BFA)和BAT算法(BA) (HBB))来优化和调度住宅消费者的电器。利用BFA、BA和HBB技术对设备进行调度,找出最优解。电器有不同的额定功率和功耗模式。本文选取了5分钟、30分钟和60分钟三种不同的运行时间间隔,并对其进行了比较。考虑了18种电器,并将它们分为三类:可中断电器、不可中断电器和基本负荷电器。在这项工作中考虑了单一家庭场景。结果表明,该技术显著降低了电力成本和峰均比。消费者不仅应该支付更少的电费,然而,公用事业也不得不承受更少的压力,特别是在高峰时段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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