基于左下递减高度分组的智能电网电力调度

Anshu Ranjan, P. Khargonekar, S. Sahni
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引用次数: 13

摘要

考虑柔性电力负荷的调度,使峰值负荷最小化。我们解决了Alamdari等人[1]关于左下递减高度启发式调度具有已知功率需求和持续时间且具有相同最早开始时间和相同截止日期的可抢占负载的性能的猜想。具体来说,我们显示了相对于最小峰值功率负载的4/3 - 1/(3D)的紧密边界,其中D是调度间隔的持续时间。在基准条形填料数据上,左下方的高度递减启发式算法生成的调度所需的峰值功率比使用下一个拟合高度递减启发式算法生成的调度所需的峰值功率少45%。在电动和插电式混合动力汽车数据上,这两种启发式方法非常有竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart grid power scheduling via bottom left decreasing height packing
We consider the scheduling of flexible electric power loads so as to minimize the peak load. We settle a conjecture of Alamdari et al.[1] regarding the performance of the bottom left decreasing height heuristic to schedule preemptable loads with known power requirement and duration and having the same earliest start time and the same deadline. Specifically, we show a tight bound of 4/3 - 1/(3D) relative to the minimum peak power load, where D is the duration of the scheduling interval. On benchmark strip packing data, the bottom left decreasing height heuristic generated schedules that required up to 45% less peak power than required by schedules generated using the next fit decreasing height heuristic. On electric and plug-in hybrid electric vehicles data, these two heuristics are very competitive.
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