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Efficient Scheduling of Nonpreemptive Appliances for Peak Load Optimization in Smart Grid

机译:非抢占式设备的高效调度,以优化智能电网中的峰值负载

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Existing electrical grid systems have a limited amount of real-time monitoring and controlling capabilities of energy generation and consumption facilities, which trigger various technical issues including voltage overloading, demand-supply mismatch, peak load consumption, etc. Some of the primary reasons for these key issues have been identified to be the inefficient utilization of energy infrastructure and uncoordinated power consumption pattern among the consumers. In this paper, we propose a coordinated load scheduling and controlling algorithm to schedule controllable appliances with the objective to minimize peak load consumption. For this purpose, we model the problem into the strip packing problem, a well-known NP-hard problem, and discuss the applicability of existing heuristics in our problem setup. We then discuss a new offline heuristic solution, named MinPeak, specifically designed for load scheduling problem. We have conducted comprehensive simulation studies using available benchmark data sets and have performed extensive comparative analyses of the proposed algorithm with some of the well-known heuristics for strip packing problem. Furthermore, experiments have been carried out using practical electricity consumption data to evaluate the performance of the algorithm in real life. The results obtained are very encouraging in terms of reducing peak load consumption and overall efficiency of the system.
机译:现有的电网系统对能量产生和消耗设施的实时监视和控制能力有限,这会引发各种技术问题,包括电压过载,供需不匹配,峰值负载消耗等。造成这些情况的一些主要原因已经确定的关键问题是能源基础设施的利用效率低下以及消费者之间的能耗模式不协调。在本文中,我们提出了一种协调的负荷调度和控制算法来调度可控设备,以最大程度地减少峰值负荷消耗。为此,我们将问题建模为带状包装问题(一个众所周知的NP-hard问题),并讨论现有启发式方法在问题设置中的适用性。然后,我们讨论专门用于负载调度问题的名为MinPeak的新的脱机启发式解决方案。我们已经使用可用的基准数据集进行了全面的模拟研究,并使用一些众所周知的试纸条填充问题对提出的算法进行了广泛的比较分析。此外,已经使用实际的电耗数据进行了实验,以评估该算法在现实生活中的性能。就减少峰值负载消耗和系统的整体效率而言,获得的结果令人鼓舞。

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