Online Algorithms for Dynamic Matching Markets in Power Distribution Systems
Online Algorithms for Dynamic Matching Markets in Power Distribution Systems
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DOI：
10.1109/lcsys.2020.3008084
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发表时间：
2020-03
影响因子：
3
通讯作者：
Deepan Muthirayan;M. Parvania;P. Khargonekar
中科院分区：
文献类型：
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作者：
Deepan Muthirayan;M. Parvania;P. Khargonekar
这封信提出了在配电系统中的动态匹配市场的在线算法。这些算法解决了灵活的负载与可再生能源发电相匹配的问题，其目标是最大限度地提高系统中交换的社会福利。更具体地说，两个在线匹配算法提出了两个发电负荷的情况下：（i）当可再生能源发电的平均值大于灵活的负荷的平均值，（ii）当条件（i）被逆转。随着直觉，这种算法的性能下降，随着供应和需求的随机性增加，提出了两个属性来评估算法的性能。第一个属性是收敛到最优（CO），因为可再生能源发电和客户负载的潜在随机性变为零。第二个属性是偏离最优性，其被测量为可再生能源发电和客户负荷的潜在随机性的标准差的函数。第一种情况下提出的算法，以满足CO和最优性的偏差，线性变化的标准偏差的变化。然后，我们表明，第二种情况下提出的算法满足CO和最优性的偏差，在一定条件下，随着标准差的变化加上偏移量线性变化。
This letter proposes online algorithms for dynamic matching markets in power distribution systems. These algorithms address the problem of matching flexible loads with renewable generation, with the objective of maximizing social welfare of the exchange in the system. More specifically, two online matching algorithms are proposed for two generation-load scenarios: (i) when the mean of renewable generation is greater than the mean of the flexible load, and (ii) when the condition (i) is reversed. With the intuition that the performance of such algorithms degrades with increasing randomness of the supply and demand, two properties are proposed for assessing the performance of the algorithms. First property is convergence to optimality (CO) as the underlying randomness of renewable generation and customer loads goes to zero. The second property is deviation from optimality, which is measured as a function of the standard deviation of the underlying randomness of renewable generation and customer loads. The algorithm proposed for the first scenario is shown to satisfy CO and a deviation from optimality that varies linearly with the variation in the standard deviation. We then show that the algorithm proposed for the second scenario satisfies CO and a deviation from optimality that varies linearly with the variation in standard deviation plus an offset under certain condition.